Statistically significant relational data mining :

Energy Technology Data Exchange (ETDEWEB)

Berry, Jonathan W.; Leung, Vitus Joseph; Phillips, Cynthia Ann; Pinar, Ali; Robinson, David Gerald; Berger-Wolf, Tanya; Bhowmick, Sanjukta; Casleton, Emily; Kaiser, Mark; Nordman, Daniel J.; Wilson, Alyson G.

2014-02-01

This report summarizes the work performed under the project (3z(BStatitically significant relational data mining.(3y (BThe goal of the project was to add more statistical rigor to the fairly ad hoc area of data mining on graphs. Our goal was to develop better algorithms and better ways to evaluate algorithm quality. We concetrated on algorithms for community detection, approximate pattern matching, and graph similarity measures. Approximate pattern matching involves finding an instance of a relatively small pattern, expressed with tolerance, in a large graph of data observed with uncertainty. This report gathers the abstracts and references for the eight refereed publications that have appeared as part of this work. We then archive three pieces of research that have not yet been published. The first is theoretical and experimental evidence that a popular statistical measure for comparison of community assignments favors over-resolved communities over approximations to a ground truth. The second are statistically motivated methods for measuring the quality of an approximate match of a small pattern in a large graph. The third is a new probabilistic random graph model. Statisticians favor these models for graph analysis. The new local structure graph model overcomes some of the issues with popular models such as exponential random graph models and latent variable models.

Common pitfalls in statistical analysis: "P" values, statistical significance and confidence intervals

Directory of Open Access Journals (Sweden)

Priya Ranganathan

2015-01-01

Full Text Available In the second part of a series on pitfalls in statistical analysis, we look at various ways in which a statistically significant study result can be expressed. We debunk some of the myths regarding the ′P′ value, explain the importance of ′confidence intervals′ and clarify the importance of including both values in a paper

Health significance and statistical uncertainty. The value of P-value.

Science.gov (United States)

Consonni, Dario; Bertazzi, Pier Alberto

2017-10-27

The P-value is widely used as a summary statistics of scientific results. Unfortunately, there is a widespread tendency to dichotomize its value in "P0.05" ("statistically not significant"), with the former implying a "positive" result and the latter a "negative" one. To show the unsuitability of such an approach when evaluating the effects of environmental and occupational risk factors. We provide examples of distorted use of P-value and of the negative consequences for science and public health of such a black-and-white vision. The rigid interpretation of P-value as a dichotomy favors the confusion between health relevance and statistical significance, discourages thoughtful thinking, and distorts attention from what really matters, the health significance. A much better way to express and communicate scientific results involves reporting effect estimates (e.g., risks, risks ratios or risk differences) and their confidence intervals (CI), which summarize and convey both health significance and statistical uncertainty. Unfortunately, many researchers do not usually consider the whole interval of CI but only examine if it includes the null-value, therefore degrading this procedure to the same P-value dichotomy (statistical significance or not). In reporting statistical results of scientific research present effects estimates with their confidence intervals and do not qualify the P-value as "significant" or "not significant".

Permutation Tests for Stochastic Ordering and ANOVA

CERN Document Server

Basso, Dario; Salmaso, Luigi; Solari, Aldo

2009-01-01

Permutation testing for multivariate stochastic ordering and ANOVA designs is a fundamental issue in many scientific fields such as medicine, biology, pharmaceutical studies, engineering, economics, psychology, and social sciences. This book presents advanced methods and related R codes to perform complex multivariate analyses

Common pitfalls in statistical analysis: “P” values, statistical significance and confidence intervals

Science.gov (United States)

Ranganathan, Priya; Pramesh, C. S.; Buyse, Marc

2015-01-01

In the second part of a series on pitfalls in statistical analysis, we look at various ways in which a statistically significant study result can be expressed. We debunk some of the myths regarding the ‘P’ value, explain the importance of ‘confidence intervals’ and clarify the importance of including both values in a paper PMID:25878958

Comparative study between EDXRF and ASTM E572 methods using two-way ANOVA

Science.gov (United States)

Krummenauer, A.; Veit, H. M.; Zoppas-Ferreira, J.

2018-03-01

Comparison with reference method is one of the necessary requirements for the validation of non-standard methods. This comparison was made using the experiment planning technique with two-way ANOVA. In ANOVA, the results obtained using the EDXRF method, to be validated, were compared with the results obtained using the ASTM E572-13 standard test method. Fisher's tests (F-test) were used to comparative study between of the elements: molybdenum, niobium, copper, nickel, manganese, chromium and vanadium. All F-tests of the elements indicate that the null hypothesis (Ho) has not been rejected. As a result, there is no significant difference between the methods compared. Therefore, according to this study, it is concluded that the EDXRF method was approved in this method comparison requirement.

Understanding the Sampling Distribution and Its Use in Testing Statistical Significance.

Science.gov (United States)

Breunig, Nancy A.

Despite the increasing criticism of statistical significance testing by researchers, particularly in the publication of the 1994 American Psychological Association's style manual, statistical significance test results are still popular in journal articles. For this reason, it remains important to understand the logic of inferential statistics. A…

Swiss solar power statistics 2007 - Significant expansion

International Nuclear Information System (INIS)

Hostettler, T.

2008-01-01

This article presents and discusses the 2007 statistics for solar power in Switzerland. A significant number of new installations is noted as is the high production figures from newer installations. The basics behind the compilation of the Swiss solar power statistics are briefly reviewed and an overview for the period 1989 to 2007 is presented which includes figures on the number of photovoltaic plant in service and installed peak power. Typical production figures in kilowatt-hours (kWh) per installed kilowatt-peak power (kWp) are presented and discussed for installations of various sizes. Increased production after inverter replacement in older installations is noted. Finally, the general political situation in Switzerland as far as solar power is concerned are briefly discussed as are international developments.

Test for the statistical significance of differences between ROC curves

International Nuclear Information System (INIS)

Metz, C.E.; Kronman, H.B.

1979-01-01

A test for the statistical significance of observed differences between two measured Receiver Operating Characteristic (ROC) curves has been designed and evaluated. The set of observer response data for each ROC curve is assumed to be independent and to arise from a ROC curve having a form which, in the absence of statistical fluctuations in the response data, graphs as a straight line on double normal-deviate axes. To test the significance of an apparent difference between two measured ROC curves, maximum likelihood estimates of the two parameters of each curve and the associated parameter variances and covariance are calculated from the corresponding set of observer response data. An approximate Chi-square statistic with two degrees of freedom is then constructed from the differences between the parameters estimated for each ROC curve and from the variances and covariances of these estimates. This statistic is known to be truly Chi-square distributed only in the limit of large numbers of trials in the observer performance experiments. Performance of the statistic for data arising from a limited number of experimental trials was evaluated. Independent sets of rating scale data arising from the same underlying ROC curve were paired, and the fraction of differences found (falsely) significant was compared to the significance level, α, used with the test. Although test performance was found to be somewhat dependent on both the number of trials in the data and the position of the underlying ROC curve in the ROC space, the results for various significance levels showed the test to be reliable under practical experimental conditions

On detection and assessment of statistical significance of Genomic Islands

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Chaudhuri Probal

2008-04-01

Full Text Available Abstract Background Many of the available methods for detecting Genomic Islands (GIs in prokaryotic genomes use markers such as transposons, proximal tRNAs, flanking repeats etc., or they use other supervised techniques requiring training datasets. Most of these methods are primarily based on the biases in GC content or codon and amino acid usage of the islands. However, these methods either do not use any formal statistical test of significance or use statistical tests for which the critical values and the P-values are not adequately justified. We propose a method, which is unsupervised in nature and uses Monte-Carlo statistical tests based on randomly selected segments of a chromosome. Such tests are supported by precise statistical distribution theory, and consequently, the resulting P-values are quite reliable for making the decision. Results Our algorithm (named Design-Island, an acronym for Detection of Statistically Significant Genomic Island runs in two phases. Some 'putative GIs' are identified in the first phase, and those are refined into smaller segments containing horizontally acquired genes in the refinement phase. This method is applied to Salmonella typhi CT18 genome leading to the discovery of several new pathogenicity, antibiotic resistance and metabolic islands that were missed by earlier methods. Many of these islands contain mobile genetic elements like phage-mediated genes, transposons, integrase and IS elements confirming their horizontal acquirement. Conclusion The proposed method is based on statistical tests supported by precise distribution theory and reliable P-values along with a technique for visualizing statistically significant islands. The performance of our method is better than many other well known methods in terms of their sensitivity and accuracy, and in terms of specificity, it is comparable to other methods.

Increasing the statistical significance of entanglement detection in experiments.

Science.gov (United States)

Jungnitsch, Bastian; Niekamp, Sönke; Kleinmann, Matthias; Gühne, Otfried; Lu, He; Gao, Wei-Bo; Chen, Yu-Ao; Chen, Zeng-Bing; Pan, Jian-Wei

2010-05-28

Entanglement is often verified by a violation of an inequality like a Bell inequality or an entanglement witness. Considerable effort has been devoted to the optimization of such inequalities in order to obtain a high violation. We demonstrate theoretically and experimentally that such an optimization does not necessarily lead to a better entanglement test, if the statistical error is taken into account. Theoretically, we show for different error models that reducing the violation of an inequality can improve the significance. Experimentally, we observe this phenomenon in a four-photon experiment, testing the Mermin and Ardehali inequality for different levels of noise. Furthermore, we provide a way to develop entanglement tests with high statistical significance.

Testing the Difference of Correlated Agreement Coefficients for Statistical Significance

Science.gov (United States)

Gwet, Kilem L.

2016-01-01

This article addresses the problem of testing the difference between two correlated agreement coefficients for statistical significance. A number of authors have proposed methods for testing the difference between two correlated kappa coefficients, which require either the use of resampling methods or the use of advanced statistical modeling…

Robustness of S1 statistic with Hodges-Lehmann for skewed distributions

Science.gov (United States)

Ahad, Nor Aishah; Yahaya, Sharipah Soaad Syed; Yin, Lee Ping

2016-10-01

Analysis of variance (ANOVA) is a common use parametric method to test the differences in means for more than two groups when the populations are normally distributed. ANOVA is highly inefficient under the influence of non- normal and heteroscedastic settings. When the assumptions are violated, researchers are looking for alternative such as Kruskal-Wallis under nonparametric or robust method. This study focused on flexible method, S1 statistic for comparing groups using median as the location estimator. S1 statistic was modified by substituting the median with Hodges-Lehmann and the default scale estimator with the variance of Hodges-Lehmann and MADn to produce two different test statistics for comparing groups. Bootstrap method was used for testing the hypotheses since the sampling distributions of these modified S1 statistics are unknown. The performance of the proposed statistic in terms of Type I error was measured and compared against the original S1 statistic, ANOVA and Kruskal-Wallis. The propose procedures show improvement compared to the original statistic especially under extremely skewed distribution.

Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs

Energy Technology Data Exchange (ETDEWEB)

Liao, Qifeng, E-mail: liaoqf@shanghaitech.edu.cn [School of Information Science and Technology, ShanghaiTech University, Shanghai 200031 (China); Lin, Guang, E-mail: guanglin@purdue.edu [Department of Mathematics & School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 (United States)

2016-07-15

In this paper we present a reduced basis ANOVA approach for partial deferential equations (PDEs) with random inputs. The ANOVA method combined with stochastic collocation methods provides model reduction in high-dimensional parameter space through decomposing high-dimensional inputs into unions of low-dimensional inputs. In this work, to further reduce the computational cost, we investigate spatial low-rank structures in the ANOVA-collocation method, and develop efficient spatial model reduction techniques using hierarchically generated reduced bases. We present a general mathematical framework of the methodology, validate its accuracy and demonstrate its efficiency with numerical experiments.

Analysis of Variance in Statistical Image Processing

Science.gov (United States)

Kurz, Ludwik; Hafed Benteftifa, M.

1997-04-01

A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

The use of the barbell cluster ANOVA design for the assessment of Environmental Pollution (1987): a case study, Wigierski National Park, NE Poland

Energy Technology Data Exchange (ETDEWEB)

Migaszewski, Zdzislaw M. [Pedagogical University, Institute of Chemistry, Geochemistry and the Environment Div., ul. Checinska 5, 25-020 Kielce (Poland)]. E-mail: zmig@pu.kielce.pl; Galuszka, Agnieszka [Pedagogical University, Institute of Chemistry, Geochemistry and the Environment Div., ul. Checinska 5, 25-020 Kielce (Poland); Paslaski, Piotr [Central Chemical Laboratory of the Polish Geological Institute, ul. Rakowiecka 4, 00-975 Warsaw (Poland)

2005-01-01

This report presents an assessment of chemical variability in natural ecosystems of Wigierski National Park (NE Poland) derived from the calculation of geochemical baselines using a barbell cluster ANOVA design. This method enabled us to obtain statistically valid information with a minimum number of samples collected. Results of summary statistics are presented for elemental concentrations in the soil horizons-O (Ol + Ofh), -A and -B, 1- and 2-year old Pinus sylvestris L. (Scots pine) needles, pine bark and Hypogymnia physodes (L.) Nyl. (lichen) thalli, as well as pH and TOC. The scope of this study also encompassed S and C stable isotope determinations and SEM examinations on Scots pine needles. The variability for S and trace metals in soils and plant bioindicators is primarily governed by parent material lithology and to a lesser extent by anthropogenic factors. This fact enabled us to study concentrations that are close to regional background levels. - The barbell cluster ANOVA design allowed the number of samples collected to be reduced to a minimum.

Statistical Significance for Hierarchical Clustering

Science.gov (United States)

Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

2017-01-01

Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

Statistical significance of trends in monthly heavy precipitation over the US

KAUST Repository

Mahajan, Salil

2011-05-11

Trends in monthly heavy precipitation, defined by a return period of one year, are assessed for statistical significance in observations and Global Climate Model (GCM) simulations over the contiguous United States using Monte Carlo non-parametric and parametric bootstrapping techniques. The results from the two Monte Carlo approaches are found to be similar to each other, and also to the traditional non-parametric Kendall\\'s τ test, implying the robustness of the approach. Two different observational data-sets are employed to test for trends in monthly heavy precipitation and are found to exhibit consistent results. Both data-sets demonstrate upward trends, one of which is found to be statistically significant at the 95% confidence level. Upward trends similar to observations are observed in some climate model simulations of the twentieth century, but their statistical significance is marginal. For projections of the twenty-first century, a statistically significant upwards trend is observed in most of the climate models analyzed. The change in the simulated precipitation variance appears to be more important in the twenty-first century projections than changes in the mean precipitation. Stochastic fluctuations of the climate-system are found to be dominate monthly heavy precipitation as some GCM simulations show a downwards trend even in the twenty-first century projections when the greenhouse gas forcings are strong. © 2011 Springer-Verlag.

Sibling Competition & Growth Tradeoffs. Biological vs. Statistical Significance.

Science.gov (United States)

Kramer, Karen L; Veile, Amanda; Otárola-Castillo, Erik

2016-01-01

Early childhood growth has many downstream effects on future health and reproduction and is an important measure of offspring quality. While a tradeoff between family size and child growth outcomes is theoretically predicted in high-fertility societies, empirical evidence is mixed. This is often attributed to phenotypic variation in parental condition. However, inconsistent study results may also arise because family size confounds the potentially differential effects that older and younger siblings can have on young children's growth. Additionally, inconsistent results might reflect that the biological significance associated with different growth trajectories is poorly understood. This paper addresses these concerns by tracking children's monthly gains in height and weight from weaning to age five in a high fertility Maya community. We predict that: 1) as an aggregate measure family size will not have a major impact on child growth during the post weaning period; 2) competition from young siblings will negatively impact child growth during the post weaning period; 3) however because of their economic value, older siblings will have a negligible effect on young children's growth. Accounting for parental condition, we use linear mixed models to evaluate the effects that family size, younger and older siblings have on children's growth. Congruent with our expectations, it is younger siblings who have the most detrimental effect on children's growth. While we find statistical evidence of a quantity/quality tradeoff effect, the biological significance of these results is negligible in early childhood. Our findings help to resolve why quantity/quality studies have had inconsistent results by showing that sibling competition varies with sibling age composition, not just family size, and that biological significance is distinct from statistical significance.

Sibling Competition & Growth Tradeoffs. Biological vs. Statistical Significance.

Directory of Open Access Journals (Sweden)

Karen L Kramer

Full Text Available Early childhood growth has many downstream effects on future health and reproduction and is an important measure of offspring quality. While a tradeoff between family size and child growth outcomes is theoretically predicted in high-fertility societies, empirical evidence is mixed. This is often attributed to phenotypic variation in parental condition. However, inconsistent study results may also arise because family size confounds the potentially differential effects that older and younger siblings can have on young children's growth. Additionally, inconsistent results might reflect that the biological significance associated with different growth trajectories is poorly understood. This paper addresses these concerns by tracking children's monthly gains in height and weight from weaning to age five in a high fertility Maya community. We predict that: 1 as an aggregate measure family size will not have a major impact on child growth during the post weaning period; 2 competition from young siblings will negatively impact child growth during the post weaning period; 3 however because of their economic value, older siblings will have a negligible effect on young children's growth. Accounting for parental condition, we use linear mixed models to evaluate the effects that family size, younger and older siblings have on children's growth. Congruent with our expectations, it is younger siblings who have the most detrimental effect on children's growth. While we find statistical evidence of a quantity/quality tradeoff effect, the biological significance of these results is negligible in early childhood. Our findings help to resolve why quantity/quality studies have had inconsistent results by showing that sibling competition varies with sibling age composition, not just family size, and that biological significance is distinct from statistical significance.

Increasing the statistical significance of entanglement detection in experiments

Energy Technology Data Exchange (ETDEWEB)

Jungnitsch, Bastian; Niekamp, Soenke; Kleinmann, Matthias; Guehne, Otfried [Institut fuer Quantenoptik und Quanteninformation, Innsbruck (Austria); Lu, He; Gao, Wei-Bo; Chen, Zeng-Bing [Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei (China); Chen, Yu-Ao; Pan, Jian-Wei [Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei (China); Physikalisches Institut, Universitaet Heidelberg (Germany)

2010-07-01

Entanglement is often verified by a violation of an inequality like a Bell inequality or an entanglement witness. Considerable effort has been devoted to the optimization of such inequalities in order to obtain a high violation. We demonstrate theoretically and experimentally that such an optimization does not necessarily lead to a better entanglement test, if the statistical error is taken into account. Theoretically, we show for different error models that reducing the violation of an inequality can improve the significance. We show this to be the case for an error model in which the variance of an observable is interpreted as its error and for the standard error model in photonic experiments. Specifically, we demonstrate that the Mermin inequality yields a Bell test which is statistically more significant than the Ardehali inequality in the case of a photonic four-qubit state that is close to a GHZ state. Experimentally, we observe this phenomenon in a four-photon experiment, testing the above inequalities for different levels of noise.

Introduction to Statistics - eNotes

DEFF Research Database (Denmark)

Brockhoff, Per B.; Møller, Jan Kloppenborg; Andersen, Elisabeth Wreford

2015-01-01

Online textbook used in the introductory statistics courses at DTU. It provides a basic introduction to applied statistics for engineers. The necessary elements from probability theory are introduced (stochastic variable, density and distribution function, mean and variance, etc.) and thereafter...... the most basic statistical analysis methods are presented: Confidence band, hypothesis testing, simulation, simple and muliple regression, ANOVA and analysis of contingency tables. Examples with the software R are included for all presented theory and methods....

Reporting effect sizes as a supplement to statistical significance ...

African Journals Online (AJOL)

The purpose of the article is to review the statistical significance reporting practices in reading instruction studies and to provide guidelines for when to calculate and report effect sizes in educational research. A review of six readily accessible (online) and accredited journals publishing research on reading instruction ...

Practical statistics in pain research.

Science.gov (United States)

Kim, Tae Kyun

2017-10-01

Pain is subjective, while statistics related to pain research are objective. This review was written to help researchers involved in pain research make statistical decisions. The main issues are related with the level of scales that are often used in pain research, the choice of statistical methods between parametric or nonparametric statistics, and problems which arise from repeated measurements. In the field of pain research, parametric statistics used to be applied in an erroneous way. This is closely related with the scales of data and repeated measurements. The level of scales includes nominal, ordinal, interval, and ratio scales. The level of scales affects the choice of statistics between parametric or non-parametric methods. In the field of pain research, the most frequently used pain assessment scale is the ordinal scale, which would include the visual analogue scale (VAS). There used to be another view, however, which considered the VAS to be an interval or ratio scale, so that the usage of parametric statistics would be accepted practically in some cases. Repeated measurements of the same subjects always complicates statistics. It means that measurements inevitably have correlations between each other, and would preclude the application of one-way ANOVA in which independence between the measurements is necessary. Repeated measures of ANOVA (RMANOVA), however, would permit the comparison between the correlated measurements as long as the condition of sphericity assumption is satisfied. Conclusively, parametric statistical methods should be used only when the assumptions of parametric statistics, such as normality and sphericity, are established.

Why we should use simpler models if the data allow this: relevance for ANOVA designs in experimental biology

Directory of Open Access Journals (Sweden)

Lazic Stanley E

2008-07-01

Full Text Available Abstract Background Analysis of variance (ANOVA is a common statistical technique in physiological research, and often one or more of the independent/predictor variables such as dose, time, or age, can be treated as a continuous, rather than a categorical variable during analysis – even if subjects were randomly assigned to treatment groups. While this is not common, there are a number of advantages of such an approach, including greater statistical power due to increased precision, a simpler and more informative interpretation of the results, greater parsimony, and transformation of the predictor variable is possible. Results An example is given from an experiment where rats were randomly assigned to receive either 0, 60, 180, or 240 mg/L of fluoxetine in their drinking water, with performance on the forced swim test as the outcome measure. Dose was treated as either a categorical or continuous variable during analysis, with the latter analysis leading to a more powerful test (p = 0.021 vs. p = 0.159. This will be true in general, and the reasons for this are discussed. Conclusion There are many advantages to treating variables as continuous numeric variables if the data allow this, and this should be employed more often in experimental biology. Failure to use the optimal analysis runs the risk of missing significant effects or relationships.

Your Chi-Square Test Is Statistically Significant: Now What?

Science.gov (United States)

Sharpe, Donald

2015-01-01

Applied researchers have employed chi-square tests for more than one hundred years. This paper addresses the question of how one should follow a statistically significant chi-square test result in order to determine the source of that result. Four approaches were evaluated: calculating residuals, comparing cells, ransacking, and partitioning. Data…

Group-wise ANOVA simultaneous component analysis for designed omics experiments

NARCIS (Netherlands)

Saccenti, Edoardo; Smilde, Age K.; Camacho, José

2018-01-01

Introduction: Modern omics experiments pertain not only to the measurement of many variables but also follow complex experimental designs where many factors are manipulated at the same time. This data can be conveniently analyzed using multivariate tools like ANOVA-simultaneous component analysis

ANOVA-HDMR structure of the higher order nodal diffusion solution

International Nuclear Information System (INIS)

Bokov, P. M.; Prinsloo, R. H.; Tomasevic, D. I.

2013-01-01

Nodal diffusion methods still represent a standard in global reactor calculations, but employ some ad-hoc approximations (such as the quadratic leakage approximation) which limit their accuracy in cases where reference quality solutions are sought. In this work we solve the nodal diffusion equations utilizing the so-called higher-order nodal methods to generate reference quality solutions and to decompose the obtained solutions via a technique known as High Dimensional Model Representation (HDMR). This representation and associated decomposition of the solution provides a new formulation of the transverse leakage term. The HDMR structure is investigated via the technique of Analysis of Variance (ANOVA), which indicates why the existing class of transversely-integrated nodal methods prove to be so successful. Furthermore, the analysis leads to a potential solution method for generating reference quality solutions at a much reduced calculational cost, by applying the ANOVA technique to the full higher order solution. (authors)

Confidence intervals permit, but don't guarantee, better inference than statistical significance testing

Directory of Open Access Journals (Sweden)

Melissa Coulson

2010-07-01

Full Text Available A statistically significant result, and a non-significant result may differ little, although significance status may tempt an interpretation of difference. Two studies are reported that compared interpretation of such results presented using null hypothesis significance testing (NHST, or confidence intervals (CIs. Authors of articles published in psychology, behavioural neuroscience, and medical journals were asked, via email, to interpret two fictitious studies that found similar results, one statistically significant, and the other non-significant. Responses from 330 authors varied greatly, but interpretation was generally poor, whether results were presented as CIs or using NHST. However, when interpreting CIs respondents who mentioned NHST were 60% likely to conclude, unjustifiably, the two results conflicted, whereas those who interpreted CIs without reference to NHST were 95% likely to conclude, justifiably, the two results were consistent. Findings were generally similar for all three disciplines. An email survey of academic psychologists confirmed that CIs elicit better interpretations if NHST is not invoked. Improved statistical inference can result from encouragement of meta-analytic thinking and use of CIs but, for full benefit, such highly desirable statistical reform requires also that researchers interpret CIs without recourse to NHST.

Testing statistical significance scores of sequence comparison methods with structure similarity

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Leunissen Jack AM

2006-10-01

Full Text Available Abstract Background In the past years the Smith-Waterman sequence comparison algorithm has gained popularity due to improved implementations and rapidly increasing computing power. However, the quality and sensitivity of a database search is not only determined by the algorithm but also by the statistical significance testing for an alignment. The e-value is the most commonly used statistical validation method for sequence database searching. The CluSTr database and the Protein World database have been created using an alternative statistical significance test: a Z-score based on Monte-Carlo statistics. Several papers have described the superiority of the Z-score as compared to the e-value, using simulated data. We were interested if this could be validated when applied to existing, evolutionary related protein sequences. Results All experiments are performed on the ASTRAL SCOP database. The Smith-Waterman sequence comparison algorithm with both e-value and Z-score statistics is evaluated, using ROC, CVE and AP measures. The BLAST and FASTA algorithms are used as reference. We find that two out of three Smith-Waterman implementations with e-value are better at predicting structural similarities between proteins than the Smith-Waterman implementation with Z-score. SSEARCH especially has very high scores. Conclusion The compute intensive Z-score does not have a clear advantage over the e-value. The Smith-Waterman implementations give generally better results than their heuristic counterparts. We recommend using the SSEARCH algorithm combined with e-values for pairwise sequence comparisons.

Statistical significance versus clinical relevance.

Science.gov (United States)

van Rijn, Marieke H C; Bech, Anneke; Bouyer, Jean; van den Brand, Jan A J G

2017-04-01

In March this year, the American Statistical Association (ASA) posted a statement on the correct use of P-values, in response to a growing concern that the P-value is commonly misused and misinterpreted. We aim to translate these warnings given by the ASA into a language more easily understood by clinicians and researchers without a deep background in statistics. Moreover, we intend to illustrate the limitations of P-values, even when used and interpreted correctly, and bring more attention to the clinical relevance of study findings using two recently reported studies as examples. We argue that P-values are often misinterpreted. A common mistake is saying that P < 0.05 means that the null hypothesis is false, and P ≥0.05 means that the null hypothesis is true. The correct interpretation of a P-value of 0.05 is that if the null hypothesis were indeed true, a similar or more extreme result would occur 5% of the times upon repeating the study in a similar sample. In other words, the P-value informs about the likelihood of the data given the null hypothesis and not the other way around. A possible alternative related to the P-value is the confidence interval (CI). It provides more information on the magnitude of an effect and the imprecision with which that effect was estimated. However, there is no magic bullet to replace P-values and stop erroneous interpretation of scientific results. Scientists and readers alike should make themselves familiar with the correct, nuanced interpretation of statistical tests, P-values and CIs. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Statistical significance of epidemiological data. Seminar: Evaluation of epidemiological studies

International Nuclear Information System (INIS)

Weber, K.H.

1993-01-01

In stochastic damages, the numbers of events, e.g. the persons who are affected by or have died of cancer, and thus the relative frequencies (incidence or mortality) are binomially distributed random variables. Their statistical fluctuations can be characterized by confidence intervals. For epidemiologic questions, especially for the analysis of stochastic damages in the low dose range, the following issues are interesting: - Is a sample (a group of persons) with a definite observed damage frequency part of the whole population? - Is an observed frequency difference between two groups of persons random or statistically significant? - Is an observed increase or decrease of the frequencies with increasing dose random or statistically significant and how large is the regression coefficient (= risk coefficient) in this case? These problems can be solved by sttistical tests. So-called distribution-free tests and tests which are not bound to the supposition of normal distribution are of particular interest, such as: - χ 2 -independence test (test in contingency tables); - Fisher-Yates-test; - trend test according to Cochran; - rank correlation test given by Spearman. These tests are explained in terms of selected epidemiologic data, e.g. of leukaemia clusters, of the cancer mortality of the Japanese A-bomb survivors especially in the low dose range as well as on the sample of the cancer mortality in the high background area in Yangjiang (China). (orig.) [de

Statistical Significance and Effect Size: Two Sides of a Coin.

Science.gov (United States)

Fan, Xitao

This paper suggests that statistical significance testing and effect size are two sides of the same coin; they complement each other, but do not substitute for one another. Good research practice requires that both should be taken into consideration to make sound quantitative decisions. A Monte Carlo simulation experiment was conducted, and a…

Publication of statistically significant research findings in prosthodontics & implant dentistry in the context of other dental specialties.

Science.gov (United States)

Papageorgiou, Spyridon N; Kloukos, Dimitrios; Petridis, Haralampos; Pandis, Nikolaos

2015-10-01

To assess the hypothesis that there is excessive reporting of statistically significant studies published in prosthodontic and implantology journals, which could indicate selective publication. The last 30 issues of 9 journals in prosthodontics and implant dentistry were hand-searched for articles with statistical analyses. The percentages of significant and non-significant results were tabulated by parameter of interest. Univariable/multivariable logistic regression analyses were applied to identify possible predictors of reporting statistically significance findings. The results of this study were compared with similar studies in dentistry with random-effects meta-analyses. From the 2323 included studies 71% of them reported statistically significant results, with the significant results ranging from 47% to 86%. Multivariable modeling identified that geographical area and involvement of statistician were predictors of statistically significant results. Compared to interventional studies, the odds that in vitro and observational studies would report statistically significant results was increased by 1.20 times (OR: 2.20, 95% CI: 1.66-2.92) and 0.35 times (OR: 1.35, 95% CI: 1.05-1.73), respectively. The probability of statistically significant results from randomized controlled trials was significantly lower compared to various study designs (difference: 30%, 95% CI: 11-49%). Likewise the probability of statistically significant results in prosthodontics and implant dentistry was lower compared to other dental specialties, but this result did not reach statistical significant (P>0.05). The majority of studies identified in the fields of prosthodontics and implant dentistry presented statistically significant results. The same trend existed in publications of other specialties in dentistry. Copyright © 2015 Elsevier Ltd. All rights reserved.

Significant Statistics: Viewed with a Contextual Lens

Science.gov (United States)

Tait-McCutcheon, Sandi

2010-01-01

This paper examines the pedagogical and organisational changes three lead teachers made to their statistics teaching and learning programs. The lead teachers posed the research question: What would the effect of contextually integrating statistical investigations and literacies into other curriculum areas be on student achievement? By finding the…

Backfitting in Smoothing Spline Anova, with Application to Historical Global Temperature Data

Science.gov (United States)

Luo, Zhen

In the attempt to estimate the temperature history of the earth using the surface observations, various biases can exist. An important source of bias is the incompleteness of sampling over both time and space. There have been a few methods proposed to deal with this problem. Although they can correct some biases resulting from incomplete sampling, they have ignored some other significant biases. In this dissertation, a smoothing spline ANOVA approach which is a multivariate function estimation method is proposed to deal simultaneously with various biases resulting from incomplete sampling. Besides that, an advantage of this method is that we can get various components of the estimated temperature history with a limited amount of information stored. This method can also be used for detecting erroneous observations in the data base. The method is illustrated through an example of modeling winter surface air temperature as a function of year and location. Extension to more complicated models are discussed. The linear system associated with the smoothing spline ANOVA estimates is too large to be solved by full matrix decomposition methods. A computational procedure combining the backfitting (Gauss-Seidel) algorithm and the iterative imputation algorithm is proposed. This procedure takes advantage of the tensor product structure in the data to make the computation feasible in an environment of limited memory. Various related issues are discussed, e.g., the computation of confidence intervals and the techniques to speed up the convergence of the backfitting algorithm such as collapsing and successive over-relaxation.

"What If" Analyses: Ways to Interpret Statistical Significance Test Results Using EXCEL or "R"

Science.gov (United States)

Ozturk, Elif

2012-01-01

The present paper aims to review two motivations to conduct "what if" analyses using Excel and "R" to understand the statistical significance tests through the sample size context. "What if" analyses can be used to teach students what statistical significance tests really do and in applied research either prospectively to estimate what sample size…

Effect of fasting ramadan in diabetes control status - application of extensive diabetes education, serum creatinine with HbA1c statistical ANOVA and regression models to prevent hypoglycemia.

Science.gov (United States)

Aziz, Kamran M A

2013-09-01

Ramadan fasting is an obligatory duty for Muslims. Unique physiologic and metabolic changes occur during fasting which requires adjustments of diabetes medications. Although challenging, successful fasting can be accomplished if pre-Ramadan extensive education is provided to the patients. Current research was conducted to study effective Ramadan fasting with different OHAs/insulins without significant risk of hypoglycemia in terms of HbA1c reductions after Ramadan. ANOVA model was used to assess HbA1c levels among different education statuses. Serum creatinine was used to measure renal functions. Pre-Ramadan diabetes education with alteration of therapy and dosage adjustments for OHAs/insulin was done. Regression models for HbA1c before Ramadan with FBS before sunset were also synthesized as a tool to prevent hypoglycemia and successful Ramadan fasting in future. Out of 1046 patients, 998 patients fasted successfully without any episodes of hypoglycemia. 48 patients (4.58%) experienced hypoglycemia. Χ(2) Test for CRD/CKD with hypoglycemia was also significant (p-value Ramadan diabetes management. Some relevant patents are also outlined in this paper.

Cautionary Note on Reporting Eta-Squared Values from Multifactor ANOVA Designs

Science.gov (United States)

Pierce, Charles A.; Block, Richard A.; Aguinis, Herman

2004-01-01

The authors provide a cautionary note on reporting accurate eta-squared values from multifactor analysis of variance (ANOVA) designs. They reinforce the distinction between classical and partial eta-squared as measures of strength of association. They provide examples from articles published in premier psychology journals in which the authors…

Statistical vs. Economic Significance in Economics and Econometrics: Further comments on McCloskey & Ziliak

DEFF Research Database (Denmark)

Engsted, Tom

I comment on the controversy between McCloskey & Ziliak and Hoover & Siegler on statistical versus economic significance, in the March 2008 issue of the Journal of Economic Methodology. I argue that while McCloskey & Ziliak are right in emphasizing 'real error', i.e. non-sampling error that cannot...... be eliminated through specification testing, they fail to acknowledge those areas in economics, e.g. rational expectations macroeconomics and asset pricing, where researchers clearly distinguish between statistical and economic significance and where statistical testing plays a relatively minor role in model...

Use of "t"-Test and ANOVA in Career-Technical Education Research

Science.gov (United States)

Rojewski, Jay W.; Lee, In Heok; Gemici, Sinan

2012-01-01

Use of t-tests and analysis of variance (ANOVA) procedures in published research from three scholarly journals in career and technical education (CTE) during a recent 5-year period was examined. Information on post hoc analyses, reporting of effect size, alpha adjustments to account for multiple tests, power, and examination of assumptions…

Distinguishing between statistical significance and practical/clinical meaningfulness using statistical inference.

Science.gov (United States)

Wilkinson, Michael

2014-03-01

Decisions about support for predictions of theories in light of data are made using statistical inference. The dominant approach in sport and exercise science is the Neyman-Pearson (N-P) significance-testing approach. When applied correctly it provides a reliable procedure for making dichotomous decisions for accepting or rejecting zero-effect null hypotheses with known and controlled long-run error rates. Type I and type II error rates must be specified in advance and the latter controlled by conducting an a priori sample size calculation. The N-P approach does not provide the probability of hypotheses or indicate the strength of support for hypotheses in light of data, yet many scientists believe it does. Outcomes of analyses allow conclusions only about the existence of non-zero effects, and provide no information about the likely size of true effects or their practical/clinical value. Bayesian inference can show how much support data provide for different hypotheses, and how personal convictions should be altered in light of data, but the approach is complicated by formulating probability distributions about prior subjective estimates of population effects. A pragmatic solution is magnitude-based inference, which allows scientists to estimate the true magnitude of population effects and how likely they are to exceed an effect magnitude of practical/clinical importance, thereby integrating elements of subjective Bayesian-style thinking. While this approach is gaining acceptance, progress might be hastened if scientists appreciate the shortcomings of traditional N-P null hypothesis significance testing.

Codon Deviation Coefficient: a novel measure for estimating codon usage bias and its statistical significance

Directory of Open Access Journals (Sweden)

Zhang Zhang

2012-03-01

Full Text Available Abstract Background Genetic mutation, selective pressure for translational efficiency and accuracy, level of gene expression, and protein function through natural selection are all believed to lead to codon usage bias (CUB. Therefore, informative measurement of CUB is of fundamental importance to making inferences regarding gene function and genome evolution. However, extant measures of CUB have not fully accounted for the quantitative effect of background nucleotide composition and have not statistically evaluated the significance of CUB in sequence analysis. Results Here we propose a novel measure--Codon Deviation Coefficient (CDC--that provides an informative measurement of CUB and its statistical significance without requiring any prior knowledge. Unlike previous measures, CDC estimates CUB by accounting for background nucleotide compositions tailored to codon positions and adopts the bootstrapping to assess the statistical significance of CUB for any given sequence. We evaluate CDC by examining its effectiveness on simulated sequences and empirical data and show that CDC outperforms extant measures by achieving a more informative estimation of CUB and its statistical significance. Conclusions As validated by both simulated and empirical data, CDC provides a highly informative quantification of CUB and its statistical significance, useful for determining comparative magnitudes and patterns of biased codon usage for genes or genomes with diverse sequence compositions.

Statistics Refresher for Molecular Imaging Technologists, Part 2: Accuracy of Interpretation, Significance, and Variance.

Science.gov (United States)

Farrell, Mary Beth

2018-06-01

This article is the second part of a continuing education series reviewing basic statistics that nuclear medicine and molecular imaging technologists should understand. In this article, the statistics for evaluating interpretation accuracy, significance, and variance are discussed. Throughout the article, actual statistics are pulled from the published literature. We begin by explaining 2 methods for quantifying interpretive accuracy: interreader and intrareader reliability. Agreement among readers can be expressed simply as a percentage. However, the Cohen κ-statistic is a more robust measure of agreement that accounts for chance. The higher the κ-statistic is, the higher is the agreement between readers. When 3 or more readers are being compared, the Fleiss κ-statistic is used. Significance testing determines whether the difference between 2 conditions or interventions is meaningful. Statistical significance is usually expressed using a number called a probability ( P ) value. Calculation of P value is beyond the scope of this review. However, knowing how to interpret P values is important for understanding the scientific literature. Generally, a P value of less than 0.05 is considered significant and indicates that the results of the experiment are due to more than just chance. Variance, standard deviation (SD), confidence interval, and standard error (SE) explain the dispersion of data around a mean of a sample drawn from a population. SD is commonly reported in the literature. A small SD indicates that there is not much variation in the sample data. Many biologic measurements fall into what is referred to as a normal distribution taking the shape of a bell curve. In a normal distribution, 68% of the data will fall within 1 SD, 95% will fall within 2 SDs, and 99.7% will fall within 3 SDs. Confidence interval defines the range of possible values within which the population parameter is likely to lie and gives an idea of the precision of the statistic being

Systematic reviews of anesthesiologic interventions reported as statistically significant

DEFF Research Database (Denmark)

Imberger, Georgina; Gluud, Christian; Boylan, John

2015-01-01

statistically significant meta-analyses of anesthesiologic interventions, we used TSA to estimate power and imprecision in the context of sparse data and repeated updates. METHODS: We conducted a search to identify all systematic reviews with meta-analyses that investigated an intervention that may......: From 11,870 titles, we found 682 systematic reviews that investigated anesthesiologic interventions. In the 50 sampled meta-analyses, the median number of trials included was 8 (interquartile range [IQR], 5-14), the median number of participants was 964 (IQR, 523-1736), and the median number...

Using the Bootstrap Method for a Statistical Significance Test of Differences between Summary Histograms

Science.gov (United States)

Xu, Kuan-Man

2006-01-01

A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called cloud objects. Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.

Empirical and Statistical Evaluation of the Effectiveness of Four ...

African Journals Online (AJOL)

Akorede

ABSTRACT: Data compression is the process of reducing the size of a file to effectively ... Through the statistical analysis performed using Boxplot and ANOVA and comparison made ...... Automatic Control, Electronics and Computer Science.

A statistical procedure for the qualification of indoor dust

International Nuclear Information System (INIS)

Scapin, Valdirene O.; Scapin, Marcos A.; Ribeiro, Andreza P.; Sato, Ivone M.

2009-01-01

The materials science advance has contributed to the humanity. Notwithstanding, serious environmental and human health problems are often observed. Thereby, many worldwide researchers have focused their work to diagnose, assess and monitor several environmental systems. In this work, a statistical procedure (on a 0.05 significance level) that allows verifying if indoor dust samples have characteristics of soil/sediment is presented. Dust samples were collected from 69 residences using a domestic vacuum cleaner in four neighborhoods of the Sao Paulo metropolitan region, Brazil, between 2006 and 2008. The samples were sieved in the fractions of 150-75 (C), 75-63 (M) and <63 μm (F). The elemental concentrations were determined by X-ray fluorescence (WDXRF). Afterwards, the indoor samples results (group A) were compared to the group of 109 certificated reference materials, which included different kinds of geological matrices, such as clay, sediment, sand and sludge (group B) and to the continental crust values (group C). Initially, the Al/Si ratio was calculated for the groups (A, B, C). The variance analysis (ANOVA), followed by Tukey test, was used to find out if there was a significant difference between the concentration means of the considered groups. According to the statistical tests; the group B presented results that are considered different from others. The interquartile range (IQR) was used to detected outlier values. ANOVA was applied again and the results (p ≥ 0.05) showed equality between ratios means of the three groups. Accordingly, the results suggest that the indoor dust samples have characteristic of soil/sediment. The statistical procedure may be used as a tool to clear the information about contaminants in dust samples, since they have characteristic of soil and may be compared with values reported by environmental control organisms. (author)

P-Value, a true test of statistical significance? a cautionary note ...

African Journals Online (AJOL)

While it's not the intention of the founders of significance testing and hypothesis testing to have the two ideas intertwined as if they are complementary, the inconvenient marriage of the two practices into one coherent, convenient, incontrovertible and misinterpreted practice has dotted our standard statistics textbooks and ...

Codon Deviation Coefficient: A novel measure for estimating codon usage bias and its statistical significance

KAUST Repository

Zhang, Zhang

2012-03-22

Background: Genetic mutation, selective pressure for translational efficiency and accuracy, level of gene expression, and protein function through natural selection are all believed to lead to codon usage bias (CUB). Therefore, informative measurement of CUB is of fundamental importance to making inferences regarding gene function and genome evolution. However, extant measures of CUB have not fully accounted for the quantitative effect of background nucleotide composition and have not statistically evaluated the significance of CUB in sequence analysis.Results: Here we propose a novel measure--Codon Deviation Coefficient (CDC)--that provides an informative measurement of CUB and its statistical significance without requiring any prior knowledge. Unlike previous measures, CDC estimates CUB by accounting for background nucleotide compositions tailored to codon positions and adopts the bootstrapping to assess the statistical significance of CUB for any given sequence. We evaluate CDC by examining its effectiveness on simulated sequences and empirical data and show that CDC outperforms extant measures by achieving a more informative estimation of CUB and its statistical significance.Conclusions: As validated by both simulated and empirical data, CDC provides a highly informative quantification of CUB and its statistical significance, useful for determining comparative magnitudes and patterns of biased codon usage for genes or genomes with diverse sequence compositions. 2012 Zhang et al; licensee BioMed Central Ltd.

Statistical analysis applied to safety culture self-assessment

International Nuclear Information System (INIS)

Macedo Soares, P.P.

2002-01-01

Interviews and opinion surveys are instruments used to assess the safety culture in an organization as part of the Safety Culture Enhancement Programme. Specific statistical tools are used to analyse the survey results. This paper presents an example of an opinion survey with the corresponding application of the statistical analysis and the conclusions obtained. Survey validation, Frequency statistics, Kolmogorov-Smirnov non-parametric test, Student (T-test) and ANOVA means comparison tests and LSD post-hoc multiple comparison test, are discussed. (author)

Interpreting Statistical Significance Test Results: A Proposed New "What If" Method.

Science.gov (United States)

Kieffer, Kevin M.; Thompson, Bruce

As the 1994 publication manual of the American Psychological Association emphasized, "p" values are affected by sample size. As a result, it can be helpful to interpret the results of statistical significant tests in a sample size context by conducting so-called "what if" analyses. However, these methods can be inaccurate…

Measuring individual significant change on the Beck Depression Inventory-II through IRT-based statistics.

NARCIS (Netherlands)

Brouwer, D.; Meijer, R.R.; Zevalkink, D.J.

2013-01-01

Several researchers have emphasized that item response theory (IRT)-based methods should be preferred over classical approaches in measuring change for individual patients. In the present study we discuss and evaluate the use of IRT-based statistics to measure statistical significant individual

A Hybrid One-Way ANOVA Approach for the Robust and Efficient Estimation of Differential Gene Expression with Multiple Patterns.

Directory of Open Access Journals (Sweden)

Mohammad Manir Hossain Mollah

Full Text Available Identifying genes that are differentially expressed (DE between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA, are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt is made to develop a hybrid one-way ANOVA approach that unifies the robustness and efficiency of estimation using the minimum β-divergence method to overcome some problems that arise in the existing robust methods for both small- and large-sample cases with multiple patterns of expression.The proposed method relies on a β-weight function, which produces values between 0 and 1. The β-weight function with β = 0.2 is used as a measure of outlier detection. It assigns smaller weights (≥ 0 to outlying expressions and larger weights (≤ 1 to typical expressions. The distribution of the β-weights is used to calculate the cut-off point, which is compared to the observed β-weight of an expression to determine whether that gene expression is an outlier. This weight function plays a key role in unifying the robustness and efficiency of estimation in one-way ANOVA.Analyses of simulated gene expression profiles revealed that all eight methods (ANOVA, SAM, LIMMA, EBarrays, eLNN, KW, robust BetaEB and proposed perform almost identically for m = 2 conditions in the absence of outliers. However, the robust BetaEB method and the proposed method exhibited considerably better performance than the other six methods in the presence of outliers. In this case, the BetaEB method exhibited slightly better performance than the proposed method for the small-sample cases, but the the proposed method exhibited much better performance than the BetaEB method for both the small- and large

Strategies for Testing Statistical and Practical Significance in Detecting DIF with Logistic Regression Models

Science.gov (United States)

Fidalgo, Angel M.; Alavi, Seyed Mohammad; Amirian, Seyed Mohammad Reza

2014-01-01

This study examines three controversial aspects in differential item functioning (DIF) detection by logistic regression (LR) models: first, the relative effectiveness of different analytical strategies for detecting DIF; second, the suitability of the Wald statistic for determining the statistical significance of the parameters of interest; and…

ANOVA Based Approch for Efficient Customer Recognition: Dealing with Common Names

OpenAIRE

Saberi , Morteza; Saberi , Zahra

2015-01-01

Part 2: Artificial Intelligence for Knowledge Management; International audience; This study proposes an Analysis of Variance (ANOVA) technique that focuses on the efficient recognition of customers with common names. The continuous improvement of Information and communications technologies (ICT) has led customers to have new expectations and concerns from their related organization. These new expectations bring various difficulties for organizations’ help desk to meet their customers’ needs....

Bayesian Information Criterion as an Alternative way of Statistical Inference

Directory of Open Access Journals (Sweden)

Nadejda Yu. Gubanova

2012-05-01

Full Text Available The article treats Bayesian information criterion as an alternative to traditional methods of statistical inference, based on NHST. The comparison of ANOVA and BIC results for psychological experiment is discussed.

Quantile regression for the statistical analysis of immunological data with many non-detects

NARCIS (Netherlands)

Eilers, P.H.C.; Roder, E.; Savelkoul, H.F.J.; Wijk, van R.G.

2012-01-01

Background Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical

Thresholds for statistical and clinical significance in systematic reviews with meta-analytic methods

DEFF Research Database (Denmark)

Jakobsen, Janus Christian; Wetterslev, Jorn; Winkel, Per

2014-01-01

BACKGROUND: Thresholds for statistical significance when assessing meta-analysis results are being insufficiently demonstrated by traditional 95% confidence intervals and P-values. Assessment of intervention effects in systematic reviews with meta-analysis deserves greater rigour. METHODS......: Methodologies for assessing statistical and clinical significance of intervention effects in systematic reviews were considered. Balancing simplicity and comprehensiveness, an operational procedure was developed, based mainly on The Cochrane Collaboration methodology and the Grading of Recommendations...... Assessment, Development, and Evaluation (GRADE) guidelines. RESULTS: We propose an eight-step procedure for better validation of meta-analytic results in systematic reviews (1) Obtain the 95% confidence intervals and the P-values from both fixed-effect and random-effects meta-analyses and report the most...

Visualizing Experimental Designs for Balanced ANOVA Models using Lisp-Stat

Directory of Open Access Journals (Sweden)

Philip W. Iversen

2004-12-01

Full Text Available The structure, or Hasse, diagram described by Taylor and Hilton (1981, American Statistician provides a visual display of the relationships between factors for balanced complete experimental designs. Using the Hasse diagram, rules exist for determining the appropriate linear model, ANOVA table, expected means squares, and F-tests in the case of balanced designs. This procedure has been implemented in Lisp-Stat using a software representation of the experimental design. The user can interact with the Hasse diagram to add, change, or delete factors and see the effect on the proposed analysis. The system has potential uses in teaching and consulting.

Experimental statistics for biological sciences.

Science.gov (United States)

Bang, Heejung; Davidian, Marie

2010-01-01

In this chapter, we cover basic and fundamental principles and methods in statistics - from "What are Data and Statistics?" to "ANOVA and linear regression," which are the basis of any statistical thinking and undertaking. Readers can easily find the selected topics in most introductory statistics textbooks, but we have tried to assemble and structure them in a succinct and reader-friendly manner in a stand-alone chapter. This text has long been used in real classroom settings for both undergraduate and graduate students who do or do not major in statistical sciences. We hope that from this chapter, readers would understand the key statistical concepts and terminologies, how to design a study (experimental or observational), how to analyze the data (e.g., describe the data and/or estimate the parameter(s) and make inference), and how to interpret the results. This text would be most useful if it is used as a supplemental material, while the readers take their own statistical courses or it would serve as a great reference text associated with a manual for any statistical software as a self-teaching guide.

Intensive inpatient treatment for bulimia nervosa: Statistical and clinical significance of symptom changes.

Science.gov (United States)

Diedrich, Alice; Schlegl, Sandra; Greetfeld, Martin; Fumi, Markus; Voderholzer, Ulrich

2018-03-01

This study examines the statistical and clinical significance of symptom changes during an intensive inpatient treatment program with a strong psychotherapeutic focus for individuals with severe bulimia nervosa. 295 consecutively admitted bulimic patients were administered the Structured Interview for Anorexic and Bulimic Syndromes-Self-Rating (SIAB-S), the Eating Disorder Inventory-2 (EDI-2), the Brief Symptom Inventory (BSI), and the Beck Depression Inventory-II (BDI-II) at treatment intake and discharge. Results indicated statistically significant symptom reductions with large effect sizes regarding severity of binge eating and compensatory behavior (SIAB-S), overall eating disorder symptom severity (EDI-2), overall psychopathology (BSI), and depressive symptom severity (BDI-II) even when controlling for antidepressant medication. The majority of patients showed either reliable (EDI-2: 33.7%, BSI: 34.8%, BDI-II: 18.1%) or even clinically significant symptom changes (EDI-2: 43.2%, BSI: 33.9%, BDI-II: 56.9%). Patients with clinically significant improvement were less distressed at intake and less likely to suffer from a comorbid borderline personality disorder when compared with those who did not improve to a clinically significant extent. Findings indicate that intensive psychotherapeutic inpatient treatment may be effective in about 75% of severely affected bulimic patients. For the remaining non-responding patients, inpatient treatment might be improved through an even stronger focus on the reduction of comorbid borderline personality traits.

Improved Test Planning and Analysis Through the Use of Advanced Statistical Methods

Science.gov (United States)

Green, Lawrence L.; Maxwell, Katherine A.; Glass, David E.; Vaughn, Wallace L.; Barger, Weston; Cook, Mylan

2016-01-01

The goal of this work is, through computational simulations, to provide statistically-based evidence to convince the testing community that a distributed testing approach is superior to a clustered testing approach for most situations. For clustered testing, numerous, repeated test points are acquired at a limited number of test conditions. For distributed testing, only one or a few test points are requested at many different conditions. The statistical techniques of Analysis of Variance (ANOVA), Design of Experiments (DOE) and Response Surface Methods (RSM) are applied to enable distributed test planning, data analysis and test augmentation. The D-Optimal class of DOE is used to plan an optimally efficient single- and multi-factor test. The resulting simulated test data are analyzed via ANOVA and a parametric model is constructed using RSM. Finally, ANOVA can be used to plan a second round of testing to augment the existing data set with new data points. The use of these techniques is demonstrated through several illustrative examples. To date, many thousands of comparisons have been performed and the results strongly support the conclusion that the distributed testing approach outperforms the clustered testing approach.

Recent Literature on Whether Statistical Significance Tests Should or Should Not Be Banned.

Science.gov (United States)

Deegear, James

This paper summarizes the literature regarding statistical significant testing with an emphasis on recent literature in various discipline and literature exploring why researchers have demonstrably failed to be influenced by the American Psychological Association publication manual's encouragement to report effect sizes. Also considered are…

Probability, Statistics, and Stochastic Processes

CERN Document Server

Olofsson, Peter

2012-01-01

This book provides a unique and balanced approach to probability, statistics, and stochastic processes.   Readers gain a solid foundation in all three fields that serves as a stepping stone to more advanced investigations into each area.  The Second Edition features new coverage of analysis of variance (ANOVA), consistency and efficiency of estimators, asymptotic theory for maximum likelihood estimators, empirical distribution function and the Kolmogorov-Smirnov test, general linear models, multiple comparisons, Markov chain Monte Carlo (MCMC), Brownian motion, martingales, and

Effects of different building blocks designs on the statistical ...

African Journals Online (AJOL)

Tholang T. Mokhele

Enumeration Areas (EAs), Small Area Layers (SALs) and SubPlaces) from the 2001 census data were used as building blocks for the generation of census output areas with AZTool program in both rural and urban areas of South Africa. One way-Analysis of Variance (ANOVA) was also performed to determine statistical ...

The impact of sample non-normality on ANOVA and alternative methods.

Science.gov (United States)

Lantz, Björn

2013-05-01

In this journal, Zimmerman (2004, 2011) has discussed preliminary tests that researchers often use to choose an appropriate method for comparing locations when the assumption of normality is doubtful. The conceptual problem with this approach is that such a two-stage process makes both the power and the significance of the entire procedure uncertain, as type I and type II errors are possible at both stages. A type I error at the first stage, for example, will obviously increase the probability of a type II error at the second stage. Based on the idea of Schmider et al. (2010), which proposes that simulated sets of sample data be ranked with respect to their degree of normality, this paper investigates the relationship between population non-normality and sample non-normality with respect to the performance of the ANOVA, Brown-Forsythe test, Welch test, and Kruskal-Wallis test when used with different distributions, sample sizes, and effect sizes. The overall conclusion is that the Kruskal-Wallis test is considerably less sensitive to the degree of sample normality when populations are distinctly non-normal and should therefore be the primary tool used to compare locations when it is known that populations are not at least approximately normal. © 2012 The British Psychological Society.

Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

Science.gov (United States)

Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

2013-03-23

Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

Bringing statistics up to speed with data in analysis of lymphocyte motility.

Science.gov (United States)

Letendre, Kenneth; Donnadieu, Emmanuel; Moses, Melanie E; Cannon, Judy L

2015-01-01

Two-photon (2P) microscopy provides immunologists with 3D video of the movement of lymphocytes in vivo. Motility parameters extracted from these videos allow detailed analysis of lymphocyte motility in lymph nodes and peripheral tissues. However, standard parametric statistical analyses such as the Student's t-test are often used incorrectly, and fail to take into account confounds introduced by the experimental methods, potentially leading to erroneous conclusions about T cell motility. Here, we compare the motility of WT T cell versus PKCθ-/-, CARMA1-/-, CCR7-/-, and PTX-treated T cells. We show that the fluorescent dyes used to label T cells have significant effects on T cell motility, and we demonstrate the use of factorial ANOVA as a statistical tool that can control for these effects. In addition, researchers often choose between the use of "cell-based" parameters by averaging multiple steps of a single cell over time (e.g. cell mean speed), or "step-based" parameters, in which all steps of a cell population (e.g. instantaneous speed) are grouped without regard for the cell track. Using mixed model ANOVA, we show that we can maintain cell-based analyses without losing the statistical power of step-based data. We find that as we use additional levels of statistical control, we can more accurately estimate the speed of T cells as they move in lymph nodes as well as measure the impact of individual signaling molecules on T cell motility. As there is increasing interest in using computational modeling to understand T cell behavior in in vivo, these quantitative measures not only give us a better determination of actual T cell movement, they may prove crucial for models to generate accurate predictions about T cell behavior.

Power, effects, confidence, and significance: an investigation of statistical practices in nursing research.

Science.gov (United States)

Gaskin, Cadeyrn J; Happell, Brenda

2014-05-01

improvement. Most importantly, researchers should abandon the misleading practice of interpreting the results from inferential tests based solely on whether they are statistically significant (or not) and, instead, focus on reporting and interpreting effect sizes, confidence intervals, and significance levels. Nursing researchers also need to conduct and report a priori power analyses, and to address the issue of Type I experiment-wise error inflation in their studies. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Examining reproducibility in psychology : A hybrid method for combining a statistically significant original study and a replication

NARCIS (Netherlands)

Van Aert, R.C.M.; Van Assen, M.A.L.M.

2018-01-01

The unrealistically high rate of positive results within psychology has increased the attention to replication research. However, researchers who conduct a replication and want to statistically combine the results of their replication with a statistically significant original study encounter

A tutorial on hunting statistical significance by chasing N

Directory of Open Access Journals (Sweden)

Denes Szucs

2016-09-01

Full Text Available There is increasing concern about the replicability of studies in psychology and cognitive neuroscience. Hidden data dredging (also called p-hacking is a major contributor to this crisis because it substantially increases Type I error resulting in a much larger proportion of false positive findings than the usually expected 5%. In order to build better intuition to avoid, detect and criticise some typical problems, here I systematically illustrate the large impact of some easy to implement and so, perhaps frequent data dredging techniques on boosting false positive findings. I illustrate several forms of two special cases of data dredging. First, researchers may violate the data collection stopping rules of null hypothesis significance testing by repeatedly checking for statistical significance with various numbers of participants. Second, researchers may group participants post-hoc along potential but unplanned independent grouping variables. The first approach 'hacks' the number of participants in studies, the second approach ‘hacks’ the number of variables in the analysis. I demonstrate the high amount of false positive findings generated by these techniques with data from true null distributions. I also illustrate that it is extremely easy to introduce strong bias into data by very mild selection and re-testing. Similar, usually undocumented data dredging steps can easily lead to having 20-50%, or more false positives.

When one size does not fit all: a simple statistical method to deal with across-individual variations of effects.

Science.gov (United States)

Vindras, Philippe; Desmurget, Michel; Baraduc, Pierre

2012-01-01

In science, it is a common experience to discover that although the investigated effect is very clear in some individuals, statistical tests are not significant because the effect is null or even opposite in other individuals. Indeed, t-tests, Anovas and linear regressions compare the average effect with respect to its inter-individual variability, so that they can fail to evidence a factor that has a high effect in many individuals (with respect to the intra-individual variability). In such paradoxical situations, statistical tools are at odds with the researcher's aim to uncover any factor that affects individual behavior, and not only those with stereotypical effects. In order to go beyond the reductive and sometimes illusory description of the average behavior, we propose a simple statistical method: applying a Kolmogorov-Smirnov test to assess whether the distribution of p-values provided by individual tests is significantly biased towards zero. Using Monte-Carlo studies, we assess the power of this two-step procedure with respect to RM Anova and multilevel mixed-effect analyses, and probe its robustness when individual data violate the assumption of normality and homoscedasticity. We find that the method is powerful and robust even with small sample sizes for which multilevel methods reach their limits. In contrast to existing methods for combining p-values, the Kolmogorov-Smirnov test has unique resistance to outlier individuals: it cannot yield significance based on a high effect in one or two exceptional individuals, which allows drawing valid population inferences. The simplicity and ease of use of our method facilitates the identification of factors that would otherwise be overlooked because they affect individual behavior in significant but variable ways, and its power and reliability with small sample sizes (<30-50 individuals) suggest it as a tool of choice in exploratory studies.

When one size does not fit all: a simple statistical method to deal with across-individual variations of effects.

Directory of Open Access Journals (Sweden)

Philippe Vindras

Full Text Available In science, it is a common experience to discover that although the investigated effect is very clear in some individuals, statistical tests are not significant because the effect is null or even opposite in other individuals. Indeed, t-tests, Anovas and linear regressions compare the average effect with respect to its inter-individual variability, so that they can fail to evidence a factor that has a high effect in many individuals (with respect to the intra-individual variability. In such paradoxical situations, statistical tools are at odds with the researcher's aim to uncover any factor that affects individual behavior, and not only those with stereotypical effects. In order to go beyond the reductive and sometimes illusory description of the average behavior, we propose a simple statistical method: applying a Kolmogorov-Smirnov test to assess whether the distribution of p-values provided by individual tests is significantly biased towards zero. Using Monte-Carlo studies, we assess the power of this two-step procedure with respect to RM Anova and multilevel mixed-effect analyses, and probe its robustness when individual data violate the assumption of normality and homoscedasticity. We find that the method is powerful and robust even with small sample sizes for which multilevel methods reach their limits. In contrast to existing methods for combining p-values, the Kolmogorov-Smirnov test has unique resistance to outlier individuals: it cannot yield significance based on a high effect in one or two exceptional individuals, which allows drawing valid population inferences. The simplicity and ease of use of our method facilitates the identification of factors that would otherwise be overlooked because they affect individual behavior in significant but variable ways, and its power and reliability with small sample sizes (<30-50 individuals suggest it as a tool of choice in exploratory studies.

Statistics in the pharmacy literature.

Science.gov (United States)

Lee, Charlene M; Soin, Herpreet K; Einarson, Thomas R

2004-09-01

Research in statistical methods is essential for maintenance of high quality of the published literature. To update previous reports of the types and frequencies of statistical terms and procedures in research studies of selected professional pharmacy journals. We obtained all research articles published in 2001 in 6 journals: American Journal of Health-System Pharmacy, The Annals of Pharmacotherapy, Canadian Journal of Hospital Pharmacy, Formulary, Hospital Pharmacy, and Journal of the American Pharmaceutical Association. Two independent reviewers identified and recorded descriptive and inferential statistical terms/procedures found in the methods, results, and discussion sections of each article. Results were determined by tallying the total number of times, as well as the percentage, that each statistical term or procedure appeared in the articles. One hundred forty-four articles were included. Ninety-eight percent employed descriptive statistics; of these, 28% used only descriptive statistics. The most common descriptive statistical terms were percentage (90%), mean (74%), standard deviation (58%), and range (46%). Sixty-nine percent of the articles used inferential statistics, the most frequent being chi(2) (33%), Student's t-test (26%), Pearson's correlation coefficient r (18%), ANOVA (14%), and logistic regression (11%). Statistical terms and procedures were found in nearly all of the research articles published in pharmacy journals. Thus, pharmacy education should aim to provide current and future pharmacists with an understanding of the common statistical terms and procedures identified to facilitate the appropriate appraisal and consequential utilization of the information available in research articles.

Statistic analyses of the color experience according to the age of the observer.

Science.gov (United States)

Hunjet, Anica; Parac-Osterman, Durdica; Vucaj, Edita

2013-04-01

Psychological experience of color is a real state of the communication between the environment and color, and it will depend on the source of the light, angle of the view, and particular on the observer and his health condition. Hering's theory or a theory of the opponent processes supposes that cones, which are situated in the retina of the eye, are not sensible on the three chromatic domains (areas, fields, zones) (red, green and purple-blue), but they produce a signal based on the principle of the opposed pairs of colors. A reason of this theory depends on the fact that certain disorders of the color eyesight, which include blindness to certain colors, cause blindness to pairs of opponent colors. This paper presents a demonstration of the experience of blue and yellow tone according to the age of the observer. For the testing of the statistically significant differences in the omission in the color experience according to the color of the background we use following statistical tests: Mann-Whitnney U Test, Kruskal-Wallis ANOVA and Median test. It was proven that the differences are statistically significant in the elderly persons (older than 35 years).

Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: a simulation study

Science.gov (United States)

2014-01-01

Background Analysis of variance (ANOVA), change-score analysis (CSA) and analysis of covariance (ANCOVA) respond differently to baseline imbalance in randomized controlled trials. However, no empirical studies appear to have quantified the differential bias and precision of estimates derived from these methods of analysis, and their relative statistical power, in relation to combinations of levels of key trial characteristics. This simulation study therefore examined the relative bias, precision and statistical power of these three analyses using simulated trial data. Methods 126 hypothetical trial scenarios were evaluated (126 000 datasets), each with continuous data simulated by using a combination of levels of: treatment effect; pretest-posttest correlation; direction and magnitude of baseline imbalance. The bias, precision and power of each method of analysis were calculated for each scenario. Results Compared to the unbiased estimates produced by ANCOVA, both ANOVA and CSA are subject to bias, in relation to pretest-posttest correlation and the direction of baseline imbalance. Additionally, ANOVA and CSA are less precise than ANCOVA, especially when pretest-posttest correlation ≥ 0.3. When groups are balanced at baseline, ANCOVA is at least as powerful as the other analyses. Apparently greater power of ANOVA and CSA at certain imbalances is achieved in respect of a biased treatment effect. Conclusions Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power. PMID:24712304

An Analysis of Research Methods and Statistical Techniques Used by Doctoral Dissertation at the Education Sciences in Turkey

Science.gov (United States)

Karadag, Engin

2010-01-01

To assess research methods and analysis of statistical techniques employed by educational researchers, this study surveyed unpublished doctoral dissertation from 2003 to 2007. Frequently used research methods consisted of experimental research; a survey; a correlational study; and a case study. Descriptive statistics, t-test, ANOVA, factor…

Factors influencing medical informatics examination grade--can biorhythm, astrological sign, seasonal aspect, or bad statistics predict outcome?

Science.gov (United States)

Petrovecki, Mladen; Rahelić, Dario; Bilić-Zulle, Lidija; Jelec, Vjekoslav

2003-02-01

To investigate whether and to what extent various parameters, such as individual characteristics, computer habits, situational factors, and pseudoscientific variables, influence Medical Informatics examination grade, and how inadequate statistical analysis can lead to wrong conclusions. The study included a total of 382 second-year undergraduate students at the Rijeka University School of Medicine in the period from 1996/97 to 2000/01 academic year. After passing the Medical Informatics exam, students filled out an anonymous questionnaire about their attitude toward learning medical informatics. They were asked to grade the course organization and curriculum content, and provide their date of birth; sex; study year; high school grades; Medical Informatics examination grade, type, and term; and describe their computer habits. From these data, we determined their zodiac signs and biorhythm. Data were compared by the use of t-test, one-way ANOVA with Tukey's honest significance difference test, and randomized complete block design ANOVA. Out of 21 variables analyzed, only 10 correlated with the average grade. Students taking Medical Informatics examination in the 1998/99 academic year earned lower average grade than any other generation. Significantly higher Medical Informatics exam grade was earned by students who finished a grammar high school; owned and regularly used a computer, Internet, and e-mail (pzodiac sign, zodiac sign quality, or biorhythm cycles, except when intentionally inadequate statistics was used for data analysis. Medical Informatics examination grades correlated with general learning capacity and computer habits of students, but showed no relation to other investigated parameters, such as examination term or pseudoscientific parameters. Inadequate statistical analysis can always confirm false conclusions.

An adaptive ANOVA-based PCKF for high-dimensional nonlinear inverse modeling

Science.gov (United States)

Li, Weixuan; Lin, Guang; Zhang, Dongxiao

2014-02-01

The probabilistic collocation-based Kalman filter (PCKF) is a recently developed approach for solving inverse problems. It resembles the ensemble Kalman filter (EnKF) in every aspect-except that it represents and propagates model uncertainty by polynomial chaos expansion (PCE) instead of an ensemble of model realizations. Previous studies have shown PCKF is a more efficient alternative to EnKF for many data assimilation problems. However, the accuracy and efficiency of PCKF depends on an appropriate truncation of the PCE series. Having more polynomial chaos basis functions in the expansion helps to capture uncertainty more accurately but increases computational cost. Selection of basis functions is particularly important for high-dimensional stochastic problems because the number of polynomial chaos basis functions required to represent model uncertainty grows dramatically as the number of input parameters (random dimensions) increases. In classic PCKF algorithms, the PCE basis functions are pre-set based on users' experience. Also, for sequential data assimilation problems, the basis functions kept in PCE expression remain unchanged in different Kalman filter loops, which could limit the accuracy and computational efficiency of classic PCKF algorithms. To address this issue, we present a new algorithm that adaptively selects PCE basis functions for different problems and automatically adjusts the number of basis functions in different Kalman filter loops. The algorithm is based on adaptive functional ANOVA (analysis of variance) decomposition, which approximates a high-dimensional function with the summation of a set of low-dimensional functions. Thus, instead of expanding the original model into PCE, we implement the PCE expansion on these low-dimensional functions, which is much less costly. We also propose a new adaptive criterion for ANOVA that is more suited for solving inverse problems. The new algorithm was tested with different examples and demonstrated

Quantile regression for the statistical analysis of immunological data with many non-detects

NARCIS (Netherlands)

P.H.C. Eilers (Paul); E. Röder (Esther); H.F.J. Savelkoul (Huub); R. Gerth van Wijk (Roy)

2012-01-01

textabstractBackground: Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced

A critical discussion of null hypothesis significance testing and statistical power analysis within psychological research

DEFF Research Database (Denmark)

Jones, Allan; Sommerlund, Bo

2007-01-01

The uses of null hypothesis significance testing (NHST) and statistical power analysis within psychological research are critically discussed. The article looks at the problems of relying solely on NHST when dealing with small and large sample sizes. The use of power-analysis in estimating...... the potential error introduced by small and large samples is advocated. Power analysis is not recommended as a replacement to NHST but as an additional source of information about the phenomena under investigation. Moreover, the importance of conceptual analysis in relation to statistical analysis of hypothesis...

Default Bayes factors for ANOVA designs

NARCIS (Netherlands)

Rouder, Jeffrey N.; Morey, Richard D.; Speckman, Paul L.; Province, Jordan M.

2012-01-01

Bayes factors have been advocated as superior to p-values for assessing statistical evidence in data. Despite the advantages of Bayes factors and the drawbacks of p-values, inference by p-values is still nearly ubiquitous. One impediment to the adoption of Bayes factors is a lack of practical

Application of SPSS in ANOVA of biological statistics%SPSS方差分析在生物统计的应用

Institute of Scientific and Technical Information of China (English)

高忠江; 施树良; 李钰

2008-01-01

方差分析是生物统计中常采用的一种方法.如何使用统计分析软件进行方差分析来实现对研究结果的快速和科学的处理,获得正确的结论,是生物学研究中重要的一环.本文通过实例介绍了如何使用SPSS(Statistical Package for the Social Science or Statistic Products and Service Solution)数据分析工具进行方差分析的方法;实现了数据分析和处理的快捷、准确和直观;与Excel相比,SPSS的统计分析功能更为强大,既有利于提高数据处理效率,又降低了实验成本.

Statistical and Visualization Data Mining Tools for Foundry Production

Directory of Open Access Journals (Sweden)

M. Perzyk

2007-07-01

Full Text Available In recent years a rapid development of a new, interdisciplinary knowledge area, called data mining, is observed. Its main task is extracting useful information from previously collected large amount of data. The main possibilities and potential applications of data mining in manufacturing industry are characterized. The main types of data mining techniques are briefly discussed, including statistical, artificial intelligence, data base and visualization tools. The statistical methods and visualization methods are presented in more detail, showing their general possibilities, advantages as well as characteristic examples of applications in foundry production. Results of the author’s research are presented, aimed at validation of selected statistical tools which can be easily and effectively used in manufacturing industry. A performance analysis of ANOVA and contingency tables based methods, dedicated for determination of the most significant process parameters as well as for detection of possible interactions among them, has been made. Several numerical tests have been performed using simulated data sets, with assumed hidden relationships as well some real data, related to the strength of ductile cast iron, collected in a foundry. It is concluded that the statistical methods offer relatively easy and fairly reliable tools for extraction of that type of knowledge about foundry manufacturing processes. However, further research is needed, aimed at explanation of some imperfections of the investigated tools as well assessment of their validity for more complex tasks.

Statistical significance estimation of a signal within the GooFit framework on GPUs

Directory of Open Access Journals (Sweden)

Cristella Leonardo

2017-01-01

Full Text Available In order to test the computing capabilities of GPUs with respect to traditional CPU cores a high-statistics toy Monte Carlo technique has been implemented both in ROOT/RooFit and GooFit frameworks with the purpose to estimate the statistical significance of the structure observed by CMS close to the kinematical boundary of the J/ψϕ invariant mass in the three-body decay B+ → J/ψϕK+. GooFit is a data analysis open tool under development that interfaces ROOT/RooFit to CUDA platform on nVidia GPU. The optimized GooFit application running on GPUs hosted by servers in the Bari Tier2 provides striking speed-up performances with respect to the RooFit application parallelised on multiple CPUs by means of PROOF-Lite tool. The considerable resulting speed-up, evident when comparing concurrent GooFit processes allowed by CUDA Multi Process Service and a RooFit/PROOF-Lite process with multiple CPU workers, is presented and discussed in detail. By means of GooFit it has also been possible to explore the behaviour of a likelihood ratio test statistic in different situations in which the Wilks Theorem may or may not apply because its regularity conditions are not satisfied.

Water quality, Multivariate statistical techniques, submarine out fall, spatial variation, temporal variation

International Nuclear Information System (INIS)

Garcia, Francisco; Palacio, Carlos; Garcia, Uriel

2012-01-01

Multivariate statistical techniques were used to investigate the temporal and spatial variations of water quality at the Santa Marta coastal area where a submarine out fall that discharges 1 m3/s of domestic wastewater is located. Two-way analysis of variance (ANOVA), cluster and principal component analysis and Krigging interpolation were considered for this report. Temporal variation showed two heterogeneous periods. From December to April, and July, where the concentration of the water quality parameters is higher; the rest of the year (May, June, August-November) were significantly lower. The spatial variation reported two areas where the water quality is different, this difference is related to the proximity to the submarine out fall discharge.

Is statistical significance clinically important?--A guide to judge the clinical relevance of study findings

NARCIS (Netherlands)

Sierevelt, Inger N.; van Oldenrijk, Jakob; Poolman, Rudolf W.

2007-01-01

In this paper we describe several issues that influence the reporting of statistical significance in relation to clinical importance, since misinterpretation of p values is a common issue in orthopaedic literature. Orthopaedic research is tormented by the risks of false-positive (type I error) and

Statistical significance of theoretical predictions: A new dimension in nuclear structure theories (I)

International Nuclear Information System (INIS)

DUDEK, J; SZPAK, B; FORNAL, B; PORQUET, M-G

2011-01-01

In this and the follow-up article we briefly discuss what we believe represents one of the most serious problems in contemporary nuclear structure: the question of statistical significance of parametrizations of nuclear microscopic Hamiltonians and the implied predictive power of the underlying theories. In the present Part I, we introduce the main lines of reasoning of the so-called Inverse Problem Theory, an important sub-field in the contemporary Applied Mathematics, here illustrated on the example of the Nuclear Mean-Field Approach.

Adaptive surrogate modeling by ANOVA and sparse polynomial dimensional decomposition for global sensitivity analysis in fluid simulation

Energy Technology Data Exchange (ETDEWEB)

Tang, Kunkun, E-mail: ktg@illinois.edu [The Center for Exascale Simulation of Plasma-Coupled Combustion (XPACC), University of Illinois at Urbana–Champaign, 1308 W Main St, Urbana, IL 61801 (United States); Inria Bordeaux – Sud-Ouest, Team Cardamom, 200 avenue de la Vieille Tour, 33405 Talence (France); Congedo, Pietro M. [Inria Bordeaux – Sud-Ouest, Team Cardamom, 200 avenue de la Vieille Tour, 33405 Talence (France); Abgrall, Rémi [Institut für Mathematik, Universität Zürich, Winterthurerstrasse 190, CH-8057 Zürich (Switzerland)

2016-06-01

The Polynomial Dimensional Decomposition (PDD) is employed in this work for the global sensitivity analysis and uncertainty quantification (UQ) of stochastic systems subject to a moderate to large number of input random variables. Due to the intimate connection between the PDD and the Analysis of Variance (ANOVA) approaches, PDD is able to provide a simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to the Polynomial Chaos expansion (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of standard methods unaffordable for real engineering applications. In order to address the problem of the curse of dimensionality, this work proposes essentially variance-based adaptive strategies aiming to build a cheap meta-model (i.e. surrogate model) by employing the sparse PDD approach with its coefficients computed by regression. Three levels of adaptivity are carried out in this paper: 1) the truncated dimensionality for ANOVA component functions, 2) the active dimension technique especially for second- and higher-order parameter interactions, and 3) the stepwise regression approach designed to retain only the most influential polynomials in the PDD expansion. During this adaptive procedure featuring stepwise regressions, the surrogate model representation keeps containing few terms, so that the cost to resolve repeatedly the linear systems of the least-squares regression problem is negligible. The size of the finally obtained sparse PDD representation is much smaller than the one of the full expansion, since only significant terms are eventually retained. Consequently, a much smaller number of calls to the deterministic model is required to compute the final PDD coefficients.

Adaptive surrogate modeling by ANOVA and sparse polynomial dimensional decomposition for global sensitivity analysis in fluid simulation

International Nuclear Information System (INIS)

Tang, Kunkun; Congedo, Pietro M.; Abgrall, Rémi

2016-01-01

The Polynomial Dimensional Decomposition (PDD) is employed in this work for the global sensitivity analysis and uncertainty quantification (UQ) of stochastic systems subject to a moderate to large number of input random variables. Due to the intimate connection between the PDD and the Analysis of Variance (ANOVA) approaches, PDD is able to provide a simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to the Polynomial Chaos expansion (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of standard methods unaffordable for real engineering applications. In order to address the problem of the curse of dimensionality, this work proposes essentially variance-based adaptive strategies aiming to build a cheap meta-model (i.e. surrogate model) by employing the sparse PDD approach with its coefficients computed by regression. Three levels of adaptivity are carried out in this paper: 1) the truncated dimensionality for ANOVA component functions, 2) the active dimension technique especially for second- and higher-order parameter interactions, and 3) the stepwise regression approach designed to retain only the most influential polynomials in the PDD expansion. During this adaptive procedure featuring stepwise regressions, the surrogate model representation keeps containing few terms, so that the cost to resolve repeatedly the linear systems of the least-squares regression problem is negligible. The size of the finally obtained sparse PDD representation is much smaller than the one of the full expansion, since only significant terms are eventually retained. Consequently, a much smaller number of calls to the deterministic model is required to compute the final PDD coefficients.

Statistical Significance of the Contribution of Variables to the PCA Solution: An Alternative Permutation Strategy

Science.gov (United States)

Linting, Marielle; van Os, Bart Jan; Meulman, Jacqueline J.

2011-01-01

In this paper, the statistical significance of the contribution of variables to the principal components in principal components analysis (PCA) is assessed nonparametrically by the use of permutation tests. We compare a new strategy to a strategy used in previous research consisting of permuting the columns (variables) of a data matrix…

A Note on Comparing the Power of Test Statistics at Low Significance Levels.

Science.gov (United States)

Morris, Nathan; Elston, Robert

2011-01-01

It is an obvious fact that the power of a test statistic is dependent upon the significance (alpha) level at which the test is performed. It is perhaps a less obvious fact that the relative performance of two statistics in terms of power is also a function of the alpha level. Through numerous personal discussions, we have noted that even some competent statisticians have the mistaken intuition that relative power comparisons at traditional levels such as α = 0.05 will be roughly similar to relative power comparisons at very low levels, such as the level α = 5 × 10 -8 , which is commonly used in genome-wide association studies. In this brief note, we demonstrate that this notion is in fact quite wrong, especially with respect to comparing tests with differing degrees of freedom. In fact, at very low alpha levels the cost of additional degrees of freedom is often comparatively low. Thus we recommend that statisticians exercise caution when interpreting the results of power comparison studies which use alpha levels that will not be used in practice.

Statistical Analysis of Human Body Movement and Group Interactions in Response to Music

Science.gov (United States)

Desmet, Frank; Leman, Marc; Lesaffre, Micheline; de Bruyn, Leen

Quantification of time series that relate to physiological data is challenging for empirical music research. Up to now, most studies have focused on time-dependent responses of individual subjects in controlled environments. However, little is known about time-dependent responses of between-subject interactions in an ecological context. This paper provides new findings on the statistical analysis of group synchronicity in response to musical stimuli. Different statistical techniques were applied to time-dependent data obtained from an experiment on embodied listening in individual and group settings. Analysis of inter group synchronicity are described. Dynamic Time Warping (DTW) and Cross Correlation Function (CCF) were found to be valid methods to estimate group coherence of the resulting movements. It was found that synchronicity of movements between individuals (human-human interactions) increases significantly in the social context. Moreover, Analysis of Variance (ANOVA) revealed that the type of music is the predominant factor in both the individual and the social context.

The Influencing Factor Analysis on the Performance Evaluation of Assembly Line Balancing Problem Level 1 (SALBP-1) Based on ANOVA Method

Science.gov (United States)

Chen, Jie; Hu, Jiangnan

2017-06-01

Industry 4.0 and lean production has become the focus of manufacturing. A current issue is to analyse the performance of the assembly line balancing. This study focus on distinguishing the factors influencing the assembly line balancing. The one-way ANOVA method is applied to explore the significant degree of distinguished factors. And regression model is built to find key points. The maximal task time (tmax ), the quantity of tasks (n), and degree of convergence of precedence graph (conv) are critical for the performance of assembly line balancing. The conclusion will do a favor to the lean production in the manufacturing.

Statistical analysis of natural radiation levels inside the UNICAMP campus through the use of Geiger-Muller counter

International Nuclear Information System (INIS)

Fontolan, Juliana A.; Biral, Antonio Renato P.

2013-01-01

It is known that the distribution at time intervals of random and unrelated events leads to the Poisson distribution . This work aims to study the distribution in time intervals of events resulting from radioactive decay of atoms present in the UNICAMP where activities involving the use of ionizing radiation are performed environments . The proposal is that the distribution surveys at intervals of these events in different locations of the university are carried out through the use of a Geiger-Mueller tube . In a next step , the evaluation of distributions obtained by using non- parametric statistics (Chi- square and Kolmogorov Smirnoff) will be taken . For analyzes involving correlations we intend to use the ANOVA (Analysis of Variance) statistical tool . Measured in six different places within the Campinas , with the use of Geiger- Muller its count mode and a time window of 20 seconds was performed . Through statistical tools chi- square and Kolmogorov Smirnoff tests, using the EXCEL program , it was observed that the distributions actually refer to a Poisson distribution. Finally, the next step is to perform analyzes involving correlations using the statistical tool ANOVA

ClusterSignificance: A bioconductor package facilitating statistical analysis of class cluster separations in dimensionality reduced data

DEFF Research Database (Denmark)

Serviss, Jason T.; Gådin, Jesper R.; Eriksson, Per

2017-01-01

, e.g. genes in a specific pathway, alone can separate samples into these established classes. Despite this, the evaluation of class separations is often subjective and performed via visualization. Here we present the ClusterSignificance package; a set of tools designed to assess the statistical...... significance of class separations downstream of dimensionality reduction algorithms. In addition, we demonstrate the design and utility of the ClusterSignificance package and utilize it to determine the importance of long non-coding RNA expression in the identity of multiple hematological malignancies....

Statistical modeling of tear strength for one step fixation process of reactive printing and easy care finishing

International Nuclear Information System (INIS)

Asim, F.; Mahmood, M.

2017-01-01

Statistical modeling imparts significant role in predicting the impact of potential factors affecting the one step fixation process of reactive printing and easy care finishing. Investigation of significant factors on tear strength of cotton fabric for single step fixation of reactive printing and easy care finishing has been carried out in this research work using experimental design technique. The potential design factors were; concentration of reactive dye, concentration of crease resistant, fixation method and fixation temperature. The experiments were designed using DoE (Design of Experiment) and analyzed through software Design Expert. The detailed analysis of significant factors and interactions including ANOVA (Analysis of Variance), residuals, model accuracy and statistical model for tear strength has been presented. The interaction and contour plots of vital factors has been examined. It has been found from the statistical analysis that each factor has an interaction with other factor. Most of the investigated factors showed curvature effect on other factor. After critical examination of significant plots, quadratic model of tear strength with significant terms and their interaction at alpha = 0.05 has been developed. The calculated correlation coefficient, R2 of the developed model is 0.9056. The high values of correlation coefficient inferred that developed equation of tear strength will precisely predict the tear strength over the range of values. (author)

Statistical significance versus clinical importance: trials on exercise therapy for chronic low back pain as example.

NARCIS (Netherlands)

van Tulder, M.W.; Malmivaara, A.; Hayden, J.; Koes, B.

2007-01-01

STUDY DESIGN. Critical appraisal of the literature. OBJECIVES. The objective of this study was to assess if results of back pain trials are statistically significant and clinically important. SUMMARY OF BACKGROUND DATA. There seems to be a discrepancy between conclusions reported by authors and

Quality of reporting statistics in two Indian pharmacology journals.

Science.gov (United States)

Jaykaran; Yadav, Preeti

2011-04-01

To evaluate the reporting of the statistical methods in articles published in two Indian pharmacology journals. All original articles published since 2002 were downloaded from the journals' (Indian Journal of Pharmacology (IJP) and Indian Journal of Physiology and Pharmacology (IJPP)) website. These articles were evaluated on the basis of appropriateness of descriptive statistics and inferential statistics. Descriptive statistics was evaluated on the basis of reporting of method of description and central tendencies. Inferential statistics was evaluated on the basis of fulfilling of assumption of statistical methods and appropriateness of statistical tests. Values are described as frequencies, percentage, and 95% confidence interval (CI) around the percentages. Inappropriate descriptive statistics was observed in 150 (78.1%, 95% CI 71.7-83.3%) articles. Most common reason for this inappropriate descriptive statistics was use of mean ± SEM at the place of "mean (SD)" or "mean ± SD." Most common statistical method used was one-way ANOVA (58.4%). Information regarding checking of assumption of statistical test was mentioned in only two articles. Inappropriate statistical test was observed in 61 (31.7%, 95% CI 25.6-38.6%) articles. Most common reason for inappropriate statistical test was the use of two group test for three or more groups. Articles published in two Indian pharmacology journals are not devoid of statistical errors.

Visual classification of very fine-grained sediments: Evaluation through univariate and multivariate statistics

Science.gov (United States)

Hohn, M. Ed; Nuhfer, E.B.; Vinopal, R.J.; Klanderman, D.S.

1980-01-01

Classifying very fine-grained rocks through fabric elements provides information about depositional environments, but is subject to the biases of visual taxonomy. To evaluate the statistical significance of an empirical classification of very fine-grained rocks, samples from Devonian shales in four cored wells in West Virginia and Virginia were measured for 15 variables: quartz, illite, pyrite and expandable clays determined by X-ray diffraction; total sulfur, organic content, inorganic carbon, matrix density, bulk density, porosity, silt, as well as density, sonic travel time, resistivity, and ??-ray response measured from well logs. The four lithologic types comprised: (1) sharply banded shale, (2) thinly laminated shale, (3) lenticularly laminated shale, and (4) nonbanded shale. Univariate and multivariate analyses of variance showed that the lithologic classification reflects significant differences for the variables measured, difference that can be detected independently of stratigraphic effects. Little-known statistical methods found useful in this work included: the multivariate analysis of variance with more than one effect, simultaneous plotting of samples and variables on canonical variates, and the use of parametric ANOVA and MANOVA on ranked data. ?? 1980 Plenum Publishing Corporation.

Adaptive statistical iterative reconstruction improves image quality without affecting perfusion CT quantitation in primary colorectal cancer

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D. Prezzi

Full Text Available Objectives: To determine the effect of Adaptive Statistical Iterative Reconstruction (ASIR on perfusion CT (pCT parameter quantitation and image quality in primary colorectal cancer. Methods: Prospective observational study. Following institutional review board approval and informed consent, 32 patients with colorectal adenocarcinoma underwent pCT (100 kV, 150 mA, 120 s acquisition, axial mode. Tumour regional blood flow (BF, blood volume (BV, mean transit time (MTT and permeability surface area product (PS were determined using identical regions-of-interests for ASIR percentages of 0%, 20%, 40%, 60%, 80% and 100%. Image noise, contrast-to-noise ratio (CNR and pCT parameters were assessed across ASIR percentages. Coefficients of variation (CV, repeated measures analysis of variance (rANOVA and Spearman’ rank order correlation were performed with statistical significance at 5%. Results: With increasing ASIR percentages, image noise decreased by 33% while CNR increased by 61%; peak tumour CNR was greater than 1.5 with 60% ASIR and above. Mean BF, BV, MTT and PS differed by less than 1.8%, 2.9%, 2.5% and 2.6% across ASIR percentages. CV were 4.9%, 4.2%, 3.3% and 7.9%; rANOVA P values: 0.85, 0.62, 0.02 and 0.81 respectively. Conclusions: ASIR improves image noise and CNR without altering pCT parameters substantially. Keywords: Perfusion imaging, Multidetector computed tomography, Colorectal neoplasms, Computer-assisted image processing, Radiation dosage

Indirectional statistics and the significance of an asymmetry discovered by Birch

International Nuclear Information System (INIS)

Kendall, D.G.; Young, G.A.

1984-01-01

Birch (1982, Nature, 298, 451) reported an apparent 'statistical asymmetry of the Universe'. The authors here develop 'indirectional analysis' as a technique for investigating statistical effects of this kind and conclude that the reported effect (whatever may be its origin) is strongly supported by the observations. The estimated pole of the asymmetry is at RA 13h 30m, Dec. -37deg. The angular error in its estimation is unlikely to exceed 20-30deg. (author)

Which statistics should tropical biologists learn?

Science.gov (United States)

Loaiza Velásquez, Natalia; González Lutz, María Isabel; Monge-Nájera, Julián

2011-09-01

Tropical biologists study the richest and most endangered biodiversity in the planet, and in these times of climate change and mega-extinctions, the need for efficient, good quality research is more pressing than in the past. However, the statistical component in research published by tropical authors sometimes suffers from poor quality in data collection; mediocre or bad experimental design and a rigid and outdated view of data analysis. To suggest improvements in their statistical education, we listed all the statistical tests and other quantitative analyses used in two leading tropical journals, the Revista de Biología Tropical and Biotropica, during a year. The 12 most frequent tests in the articles were: Analysis of Variance (ANOVA), Chi-Square Test, Student's T Test, Linear Regression, Pearson's Correlation Coefficient, Mann-Whitney U Test, Kruskal-Wallis Test, Shannon's Diversity Index, Tukey's Test, Cluster Analysis, Spearman's Rank Correlation Test and Principal Component Analysis. We conclude that statistical education for tropical biologists must abandon the old syllabus based on the mathematical side of statistics and concentrate on the correct selection of these and other procedures and tests, on their biological interpretation and on the use of reliable and friendly freeware. We think that their time will be better spent understanding and protecting tropical ecosystems than trying to learn the mathematical foundations of statistics: in most cases, a well designed one-semester course should be enough for their basic requirements.

Analysis of Statistical Methods Currently used in Toxicology Journals.

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Na, Jihye; Yang, Hyeri; Bae, SeungJin; Lim, Kyung-Min

2014-09-01

Statistical methods are frequently used in toxicology, yet it is not clear whether the methods employed by the studies are used consistently and conducted based on sound statistical grounds. The purpose of this paper is to describe statistical methods used in top toxicology journals. More specifically, we sampled 30 papers published in 2014 from Toxicology and Applied Pharmacology, Archives of Toxicology, and Toxicological Science and described methodologies used to provide descriptive and inferential statistics. One hundred thirteen endpoints were observed in those 30 papers, and most studies had sample size less than 10, with the median and the mode being 6 and 3 & 6, respectively. Mean (105/113, 93%) was dominantly used to measure central tendency, and standard error of the mean (64/113, 57%) and standard deviation (39/113, 34%) were used to measure dispersion, while few studies provide justifications regarding why the methods being selected. Inferential statistics were frequently conducted (93/113, 82%), with one-way ANOVA being most popular (52/93, 56%), yet few studies conducted either normality or equal variance test. These results suggest that more consistent and appropriate use of statistical method is necessary which may enhance the role of toxicology in public health.

Prediction and Control of Cutting Tool Vibration in Cnc Lathe with Anova and Ann

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S. S. Abuthakeer

2011-06-01

Full Text Available Machining is a complex process in which many variables can deleterious the desired results. Among them, cutting tool vibration is the most critical phenomenon which influences dimensional precision of the components machined, functional behavior of the machine tools and life of the cutting tool. In a machining operation, the cutting tool vibrations are mainly influenced by cutting parameters like cutting speed, depth of cut and tool feed rate. In this work, the cutting tool vibrations are controlled using a damping pad made of Neoprene. Experiments were conducted in a CNC lathe where the tool holder is supported with and without damping pad. The cutting tool vibration signals were collected through a data acquisition system supported by LabVIEW software. To increase the buoyancy and reliability of the experiments, a full factorial experimental design was used. Experimental data collected were tested with analysis of variance (ANOVA to understand the influences of the cutting parameters. Empirical models have been developed using analysis of variance (ANOVA. Experimental studies and data analysis have been performed to validate the proposed damping system. Multilayer perceptron neural network model has been constructed with feed forward back-propagation algorithm using the acquired data. On the completion of the experimental test ANN is used to validate the results obtained and also to predict the behavior of the system under any cutting condition within the operating range. The onsite tests show that the proposed system reduces the vibration of cutting tool to a greater extend.

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry.

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Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y; Drake, Steven K; Gucek, Marjan; Sacks, David B; Yu, Yi-Kuo

2018-06-05

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html . Graphical Abstract ᅟ.

Kronecker Product Analytical Approach to ANOVA of Surface ...

African Journals Online (AJOL)

The Fishers-Yates algorithm has remained the most widely used statistical ... with Kronecker product analysis which was enhanced by the use of MATLAB ... Keywords: Kronecker product, Sum of Squares, Mean sum of squares, Optimization.

Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data.

Science.gov (United States)

Kim, Sung-Min; Choi, Yosoon

2017-06-18

To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs) in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a z -score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-ray fluorescence (PXRF) analysis, sufficient input data are acquired from the Busan abandoned mine and used for hot spot analysis. To calibrate the PXRF data, which have a relatively low accuracy, the PXRF analysis data are transformed using the inductively coupled plasma atomic emission spectrometry (ICP-AES) data. The transformed PXRF data of the Busan abandoned mine are classified into four groups according to their normalized content and z -scores: high content with a high z -score (HH), high content with a low z -score (HL), low content with a high z -score (LH), and low content with a low z -score (LL). The HL and LH cases may be due to measurement errors. Additional or complementary surveys are required for the areas surrounding these suspect samples or for significant hot spot areas. The soil sampling is conducted according to a four-phase procedure in which the hot spot analysis and proposed group classification method are employed to support the development of a sampling plan for the following phase. Overall, 30, 50, 80, and 100 samples are investigated and analyzed in phases 1-4, respectively. The method implemented in this case study may be utilized in the field for the assessment of statistically significant soil contamination and the identification of areas for which an additional survey is required.

Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data

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Sung-Min Kim

2017-06-01

Full Text Available To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a z-score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-ray fluorescence (PXRF analysis, sufficient input data are acquired from the Busan abandoned mine and used for hot spot analysis. To calibrate the PXRF data, which have a relatively low accuracy, the PXRF analysis data are transformed using the inductively coupled plasma atomic emission spectrometry (ICP-AES data. The transformed PXRF data of the Busan abandoned mine are classified into four groups according to their normalized content and z-scores: high content with a high z-score (HH, high content with a low z-score (HL, low content with a high z-score (LH, and low content with a low z-score (LL. The HL and LH cases may be due to measurement errors. Additional or complementary surveys are required for the areas surrounding these suspect samples or for significant hot spot areas. The soil sampling is conducted according to a four-phase procedure in which the hot spot analysis and proposed group classification method are employed to support the development of a sampling plan for the following phase. Overall, 30, 50, 80, and 100 samples are investigated and analyzed in phases 1–4, respectively. The method implemented in this case study may be utilized in the field for the assessment of statistically significant soil contamination and the identification of areas for which an additional survey is required.

Statistically significant faunal differences among Middle Ordovician age, Chickamauga Group bryozoan bioherms, central Alabama

Energy Technology Data Exchange (ETDEWEB)

Crow, C.J.

1985-01-01

Middle Ordovician age Chickamauga Group carbonates crop out along the Birmingham and Murphrees Valley anticlines in central Alabama. The macrofossil contents on exposed surfaces of seven bioherms have been counted to determine their various paleontologic characteristics. Twelve groups of organisms are present in these bioherms. Dominant organisms include bryozoans, algae, brachiopods, sponges, pelmatozoans, stromatoporoids and corals. Minor accessory fauna include predators, scavengers and grazers such as gastropods, ostracods, trilobites, cephalopods and pelecypods. Vertical and horizontal niche zonation has been detected for some of the bioherm dwelling fauna. No one bioherm of those studied exhibits all 12 groups of organisms; rather, individual bioherms display various subsets of the total diversity. Statistical treatment (G-test) of the diversity data indicates a lack of statistical homogeneity of the bioherms, both within and between localities. Between-locality population heterogeneity can be ascribed to differences in biologic responses to such gross environmental factors as water depth and clarity, and energy levels. At any one locality, gross aspects of the paleoenvironments are assumed to have been more uniform. Significant differences among bioherms at any one locality may have resulted from patchy distribution of species populations, differential preservation and other factors.

Detecting Statistically Significant Communities of Triangle Motifs in Undirected Networks

Science.gov (United States)

2016-04-26

Systems, Statistics & Management Science, University of Alabama, USA. 1 DISTRIBUTION A: Distribution approved for public release. Contents 1 Summary 5...13 5 Application to Real Networks 18 5.1 2012 FBS Football Schedule Network... football schedule network. . . . . . . . . . . . . . . . . . . . . . 21 14 Stem plot of degree-ordered vertices versus the degree for college football

Statistical significant changes in ground thermal conditions of alpine Austria during the last decade

Science.gov (United States)

Kellerer-Pirklbauer, Andreas

2016-04-01

Longer data series (e.g. >10 a) of ground temperatures in alpine regions are helpful to improve the understanding regarding the effects of present climate change on distribution and thermal characteristics of seasonal frost- and permafrost-affected areas. Beginning in 2004 - and more intensively since 2006 - a permafrost and seasonal frost monitoring network was established in Central and Eastern Austria by the University of Graz. This network consists of c.60 ground temperature (surface and near-surface) monitoring sites which are located at 1922-3002 m a.s.l., at latitude 46°55'-47°22'N and at longitude 12°44'-14°41'E. These data allow conclusions about general ground thermal conditions, potential permafrost occurrence, trend during the observation period, and regional pattern of changes. Calculations and analyses of several different temperature-related parameters were accomplished. At an annual scale a region-wide statistical significant warming during the observation period was revealed by e.g. an increase in mean annual temperature values (mean, maximum) or the significant lowering of the surface frost number (F+). At a seasonal scale no significant trend of any temperature-related parameter was in most cases revealed for spring (MAM) and autumn (SON). Winter (DJF) shows only a weak warming. In contrast, the summer (JJA) season reveals in general a significant warming as confirmed by several different temperature-related parameters such as e.g. mean seasonal temperature, number of thawing degree days, number of freezing degree days, or days without night frost. On a monthly basis August shows the statistically most robust and strongest warming of all months, although regional differences occur. Despite the fact that the general ground temperature warming during the last decade is confirmed by the field data in the study region, complications in trend analyses arise by temperature anomalies (e.g. warm winter 2006/07) or substantial variations in the winter

A statistical approach to optimizing concrete mixture design.

Science.gov (United States)

Ahmad, Shamsad; Alghamdi, Saeid A

2014-01-01

A step-by-step statistical approach is proposed to obtain optimum proportioning of concrete mixtures using the data obtained through a statistically planned experimental program. The utility of the proposed approach for optimizing the design of concrete mixture is illustrated considering a typical case in which trial mixtures were considered according to a full factorial experiment design involving three factors and their three levels (3(3)). A total of 27 concrete mixtures with three replicates (81 specimens) were considered by varying the levels of key factors affecting compressive strength of concrete, namely, water/cementitious materials ratio (0.38, 0.43, and 0.48), cementitious materials content (350, 375, and 400 kg/m(3)), and fine/total aggregate ratio (0.35, 0.40, and 0.45). The experimental data were utilized to carry out analysis of variance (ANOVA) and to develop a polynomial regression model for compressive strength in terms of the three design factors considered in this study. The developed statistical model was used to show how optimization of concrete mixtures can be carried out with different possible options.

A Statistical Approach to Optimizing Concrete Mixture Design

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Shamsad Ahmad

2014-01-01

Full Text Available A step-by-step statistical approach is proposed to obtain optimum proportioning of concrete mixtures using the data obtained through a statistically planned experimental program. The utility of the proposed approach for optimizing the design of concrete mixture is illustrated considering a typical case in which trial mixtures were considered according to a full factorial experiment design involving three factors and their three levels (33. A total of 27 concrete mixtures with three replicates (81 specimens were considered by varying the levels of key factors affecting compressive strength of concrete, namely, water/cementitious materials ratio (0.38, 0.43, and 0.48, cementitious materials content (350, 375, and 400 kg/m3, and fine/total aggregate ratio (0.35, 0.40, and 0.45. The experimental data were utilized to carry out analysis of variance (ANOVA and to develop a polynomial regression model for compressive strength in terms of the three design factors considered in this study. The developed statistical model was used to show how optimization of concrete mixtures can be carried out with different possible options.

Conducting tests for statistically significant differences using forest inventory data

Science.gov (United States)

James A. Westfall; Scott A. Pugh; John W. Coulston

2013-01-01

Many forest inventory and monitoring programs are based on a sample of ground plots from which estimates of forest resources are derived. In addition to evaluating metrics such as number of trees or amount of cubic wood volume, it is often desirable to make comparisons between resource attributes. To properly conduct statistical tests for differences, it is imperative...

SOCR Analyses - an Instructional Java Web-based Statistical Analysis Toolkit.

Science.gov (United States)

Chu, Annie; Cui, Jenny; Dinov, Ivo D

2009-03-01

The Statistical Online Computational Resource (SOCR) designs web-based tools for educational use in a variety of undergraduate courses (Dinov 2006). Several studies have demonstrated that these resources significantly improve students' motivation and learning experiences (Dinov et al. 2008). SOCR Analyses is a new component that concentrates on data modeling and analysis using parametric and non-parametric techniques supported with graphical model diagnostics. Currently implemented analyses include commonly used models in undergraduate statistics courses like linear models (Simple Linear Regression, Multiple Linear Regression, One-Way and Two-Way ANOVA). In addition, we implemented tests for sample comparisons, such as t-test in the parametric category; and Wilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, in the non-parametric category. SOCR Analyses also include several hypothesis test models, such as Contingency tables, Friedman's test and Fisher's exact test.The code itself is open source (http://socr.googlecode.com/), hoping to contribute to the efforts of the statistical computing community. The code includes functionality for each specific analysis model and it has general utilities that can be applied in various statistical computing tasks. For example, concrete methods with API (Application Programming Interface) have been implemented in statistical summary, least square solutions of general linear models, rank calculations, etc. HTML interfaces, tutorials, source code, activities, and data are freely available via the web (www.SOCR.ucla.edu). Code examples for developers and demos for educators are provided on the SOCR Wiki website.In this article, the pedagogical utilization of the SOCR Analyses is discussed, as well as the underlying design framework. As the SOCR project is on-going and more functions and tools are being added to it, these resources are constantly improved. The reader is strongly encouraged to check the SOCR site for most

Evaluating the statistical performance of less applied algorithms in classification of worldview-3 imagery data in an urbanized landscape

Science.gov (United States)

Ranaie, Mehrdad; Soffianian, Alireza; Pourmanafi, Saeid; Mirghaffari, Noorollah; Tarkesh, Mostafa

2018-03-01

In recent decade, analyzing the remotely sensed imagery is considered as one of the most common and widely used procedures in the environmental studies. In this case, supervised image classification techniques play a central role. Hence, taking a high resolution Worldview-3 over a mixed urbanized landscape in Iran, three less applied image classification methods including Bagged CART, Stochastic gradient boosting model and Neural network with feature extraction were tested and compared with two prevalent methods: random forest and support vector machine with linear kernel. To do so, each method was run ten time and three validation techniques was used to estimate the accuracy statistics consist of cross validation, independent validation and validation with total of train data. Moreover, using ANOVA and Tukey test, statistical difference significance between the classification methods was significantly surveyed. In general, the results showed that random forest with marginal difference compared to Bagged CART and stochastic gradient boosting model is the best performing method whilst based on independent validation there was no significant difference between the performances of classification methods. It should be finally noted that neural network with feature extraction and linear support vector machine had better processing speed than other.

Assessing a learning process with functional ANOVA estimators of EEG power spectral densities.

Science.gov (United States)

Gutiérrez, David; Ramírez-Moreno, Mauricio A

2016-04-01

We propose to assess the process of learning a task using electroencephalographic (EEG) measurements. In particular, we quantify changes in brain activity associated to the progression of the learning experience through the functional analysis-of-variances (FANOVA) estimators of the EEG power spectral density (PSD). Such functional estimators provide a sense of the effect of training in the EEG dynamics. For that purpose, we implemented an experiment to monitor the process of learning to type using the Colemak keyboard layout during a twelve-lessons training. Hence, our aim is to identify statistically significant changes in PSD of various EEG rhythms at different stages and difficulty levels of the learning process. Those changes are taken into account only when a probabilistic measure of the cognitive state ensures the high engagement of the volunteer to the training. Based on this, a series of statistical tests are performed in order to determine the personalized frequencies and sensors at which changes in PSD occur, then the FANOVA estimates are computed and analyzed. Our experimental results showed a significant decrease in the power of [Formula: see text] and [Formula: see text] rhythms for ten volunteers during the learning process, and such decrease happens regardless of the difficulty of the lesson. These results are in agreement with previous reports of changes in PSD being associated to feature binding and memory encoding.

ANOVA IN MARKETING RESEARCH OF CONSUMER BEHAVIOR OF DIFFERENT CATEGORIES IN GEORGIAN MARKET

Directory of Open Access Journals (Sweden)

NUGZAR TODUA

2015-03-01

Full Text Available Consumer behavior research was conducted on bank services and (non-alcohol soft drinks. Based on four different currencies and ten services there are analyses made on bank clients’ distribution by bank services and currencies, percentage distribution by bank services, percentage distribution of bank services by currencies. Similar results are also received in case of ten soft drinks with their five characteristics: consumers quantities split by types of soft drinks and attributes; Attributes percentage split by types of soft drinks; Types of soft drinks percentage split by attributes. With usage of ANOVA, based on the marketing research outcomes it is concluded that bank clients’ total quantities i.e. populations’ unknown mean scores do not differ from each other. In the soft drinks research case consumers’ total quantities i.e. populations’ unknown mean scores vary by characteristics

What Do Deep Statistical Analysis on Gaming Motivation and Game Characteristics Clusters Reveal about Targeting Demographics when Designing Gamified Contents?

Directory of Open Access Journals (Sweden)

Alireza Tavakkoli

2015-06-01

Full Text Available This paper presents the comprehensive results of the study of a cohort of college graduate and undergraduate students who participated in playing a Massively Multiplayer Online Role Playing Game (MMORPG as a gameplay rich with social interaction as well as intellectual and aesthetic features. We present the full results of the study in the form of inferential statistics and a review of our descriptive statistics previously reported in [46]. Separate one-way independent-measures multivariate analysis of variance (MANOVA's were used to analyze the data from several instruments to determine if there were statistically significant differences first by gender, then by age group, and then by degree. Moreover, a one-way repeated-measures analysis of variance (ANOVA was used to determine if there was a statistically significant difference between the clusters in the 5 gaming clusters on the Game Characteristic Survey. Follow-up paired samples t-tests were used to see if there was a statistically significant difference between each of the 10 possible combinations of paired clusters. Our results support the hypotheses and outline the features that may need to be taken into account in support of tailoring gamified educational content targeting a certain demographic. Sections 1, 2, and 3 below from our pervious study [46] are included because this is the second part of the two-part study. [46] Tavakkoli, A., Loffredo, D., Ward, M., Sr. (2014. "Insights from Massively Multiplayer Online Role Playing Games to Enhance Gamification in Education", Journal of Systemics, Cybernetics, and Informatics, 12(4, 66-78.

The distribution of P-values in medical research articles suggested selective reporting associated with statistical significance.

Science.gov (United States)

Perneger, Thomas V; Combescure, Christophe

2017-07-01

Published P-values provide a window into the global enterprise of medical research. The aim of this study was to use the distribution of published P-values to estimate the relative frequencies of null and alternative hypotheses and to seek irregularities suggestive of publication bias. This cross-sectional study included P-values published in 120 medical research articles in 2016 (30 each from the BMJ, JAMA, Lancet, and New England Journal of Medicine). The observed distribution of P-values was compared with expected distributions under the null hypothesis (i.e., uniform between 0 and 1) and the alternative hypothesis (strictly decreasing from 0 to 1). P-values were categorized according to conventional levels of statistical significance and in one-percent intervals. Among 4,158 recorded P-values, 26.1% were highly significant (P values values equal to 1, and (3) about twice as many P-values less than 0.05 compared with those more than 0.05. The latter finding was seen in both randomized trials and observational studies, and in most types of analyses, excepting heterogeneity tests and interaction tests. Under plausible assumptions, we estimate that about half of the tested hypotheses were null and the other half were alternative. This analysis suggests that statistical tests published in medical journals are not a random sample of null and alternative hypotheses but that selective reporting is prevalent. In particular, significant results are about twice as likely to be reported as nonsignificant results. Copyright © 2017 Elsevier Inc. All rights reserved.

Excel 2016 in applied statistics for high school students a guide to solving practical problems

CERN Document Server

Quirk, Thomas J

2018-01-01

This textbook is a step-by-step guide for high school, community college, or undergraduate students who are taking a course in applied statistics and wish to learn how to use Excel to solve statistical problems. All of the statistics problems in this book will come from the following fields of study: business, education, psychology, marketing, engineering and advertising. Students will learn how to perform key statistical tests in Excel without being overwhelmed by statistical theory. Each chapter briefly explains a topic and then demonstrates how to use Excel commands and formulas to solve specific statistics problems. This book gives practice in using Excel in two different ways: (1) writing formulas (e.g., confidence interval about the mean, one-group t-test, two-group t-test, correlation) and (2) using Excel’s drop-down formula menus (e.g., simple linear regression, multiple correlations and multiple regression, and one-way ANOVA). Three practice problems are provided at the end of each chapter, along w...

Biomarker Detection in Association Studies: Modeling SNPs Simultaneously via Logistic ANOVA

KAUST Repository

Jung, Yoonsuh

2014-10-02

In genome-wide association studies, the primary task is to detect biomarkers in the form of Single Nucleotide Polymorphisms (SNPs) that have nontrivial associations with a disease phenotype and some other important clinical/environmental factors. However, the extremely large number of SNPs comparing to the sample size inhibits application of classical methods such as the multiple logistic regression. Currently the most commonly used approach is still to analyze one SNP at a time. In this paper, we propose to consider the genotypes of the SNPs simultaneously via a logistic analysis of variance (ANOVA) model, which expresses the logit transformed mean of SNP genotypes as the summation of the SNP effects, effects of the disease phenotype and/or other clinical variables, and the interaction effects. We use a reduced-rank representation of the interaction-effect matrix for dimensionality reduction, and employ the L 1-penalty in a penalized likelihood framework to filter out the SNPs that have no associations. We develop a Majorization-Minimization algorithm for computational implementation. In addition, we propose a modified BIC criterion to select the penalty parameters and determine the rank number. The proposed method is applied to a Multiple Sclerosis data set and simulated data sets and shows promise in biomarker detection.

Biomarker Detection in Association Studies: Modeling SNPs Simultaneously via Logistic ANOVA

KAUST Repository

Jung, Yoonsuh; Huang, Jianhua Z.; Hu, Jianhua

2014-01-01

In genome-wide association studies, the primary task is to detect biomarkers in the form of Single Nucleotide Polymorphisms (SNPs) that have nontrivial associations with a disease phenotype and some other important clinical/environmental factors. However, the extremely large number of SNPs comparing to the sample size inhibits application of classical methods such as the multiple logistic regression. Currently the most commonly used approach is still to analyze one SNP at a time. In this paper, we propose to consider the genotypes of the SNPs simultaneously via a logistic analysis of variance (ANOVA) model, which expresses the logit transformed mean of SNP genotypes as the summation of the SNP effects, effects of the disease phenotype and/or other clinical variables, and the interaction effects. We use a reduced-rank representation of the interaction-effect matrix for dimensionality reduction, and employ the L 1-penalty in a penalized likelihood framework to filter out the SNPs that have no associations. We develop a Majorization-Minimization algorithm for computational implementation. In addition, we propose a modified BIC criterion to select the penalty parameters and determine the rank number. The proposed method is applied to a Multiple Sclerosis data set and simulated data sets and shows promise in biomarker detection.

Absolute variation of the mechanical characteristics of halloysite reinforced polyurethane nanocomposites complemented by Taguchi and ANOVA approaches

Science.gov (United States)

Gaaz, Tayser Sumer; Sulong, Abu Bakar; Kadhum, Abdul Amir H.; Nassir, Mohamed H.; Al-Amiery, Ahmed A.

The variation of the results of the mechanical properties of halloysite nanotubes (HNTs) reinforced thermoplastic polyurethane (TPU) at different HNTs loadings was implemented as a tool for analysis. The preparation of HNTs-TPU nanocomposites was performed under four controlled parameters of mixing temperature, mixing speed, mixing time, and HNTs loading at three levels each to satisfy Taguchi method orthogonal array L9 aiming to optimize these parameters for the best measurements of tensile strength, Young's modulus, and tensile strain (known as responses). The maximum variation of the experimental results for each response was determined and analysed based on the optimized results predicted by Taguchi method and ANOVA. It was found that the maximum absolute variations of the three mentioned responses are 69%, 352%, and 126%, respectively. The analysis has shown that the preparation of the optimized tensile strength requires 1 wt.% HNTs loading (excluding 2 wt.% and 3 wt.%), mixing temperature of 190 °C (excluding 200 °C and 210 °C), and mixing speed of 30 rpm (excluding 40 rpm and 50 rpm). In addition, the analysis has determined that the mixing time at 20 min has no effect on the preparation. The mentioned analysis was fortified by ANOVA, images of FESEM, and DSC results. Seemingly, the agglomeration and distribution of HNTs in the nanocomposite play an important role in the process. The outcome of the analysis could be considered as a very important step towards the reliability of Taguchi method.

Predicting axillary lymph node metastasis from kinetic statistics of DCE-MRI breast images

Science.gov (United States)

Ashraf, Ahmed B.; Lin, Lilie; Gavenonis, Sara C.; Mies, Carolyn; Xanthopoulos, Eric; Kontos, Despina

2012-03-01

The presence of axillary lymph node metastases is the most important prognostic factor in breast cancer and can influence the selection of adjuvant therapy, both chemotherapy and radiotherapy. In this work we present a set of kinetic statistics derived from DCE-MRI for predicting axillary node status. Breast DCE-MRI images from 69 women with known nodal status were analyzed retrospectively under HIPAA and IRB approval. Axillary lymph nodes were positive in 12 patients while 57 patients had no axillary lymph node involvement. Kinetic curves for each pixel were computed and a pixel-wise map of time-to-peak (TTP) was obtained. Pixels were first partitioned according to the similarity of their kinetic behavior, based on TTP values. For every kinetic curve, the following pixel-wise features were computed: peak enhancement (PE), wash-in-slope (WIS), wash-out-slope (WOS). Partition-wise statistics for every feature map were calculated, resulting in a total of 21 kinetic statistic features. ANOVA analysis was done to select features that differ significantly between node positive and node negative women. Using the computed kinetic statistic features a leave-one-out SVM classifier was learned that performs with AUC=0.77 under the ROC curve, outperforming the conventional kinetic measures, including maximum peak enhancement (MPE) and signal enhancement ratio (SER), (AUCs of 0.61 and 0.57 respectively). These findings suggest that our DCE-MRI kinetic statistic features can be used to improve the prediction of axillary node status in breast cancer patients. Such features could ultimately be used as imaging biomarkers to guide personalized treatment choices for women diagnosed with breast cancer.

Sigsearch: a new term for post hoc unplanned search for statistically significant relationships with the intent to create publishable findings.

Science.gov (United States)

Hashim, Muhammad Jawad

2010-09-01

Post-hoc secondary data analysis with no prespecified hypotheses has been discouraged by textbook authors and journal editors alike. Unfortunately no single term describes this phenomenon succinctly. I would like to coin the term "sigsearch" to define this practice and bring it within the teaching lexicon of statistics courses. Sigsearch would include any unplanned, post-hoc search for statistical significance using multiple comparisons of subgroups. It would also include data analysis with outcomes other than the prespecified primary outcome measure of a study as well as secondary data analyses of earlier research.

A method of statistical analysis in the field of sports science when assumptions of parametric tests are not violated

Directory of Open Access Journals (Sweden)

Elżbieta Sandurska

2016-12-01

Full Text Available Introduction: Application of statistical software typically does not require extensive statistical knowledge, allowing to easily perform even complex analyses. Consequently, test selection criteria and important assumptions may be easily overlooked or given insufficient consideration. In such cases, the results may likely lead to wrong conclusions. Aim: To discuss issues related to assumption violations in the case of Student's t-test and one-way ANOVA, two parametric tests frequently used in the field of sports science, and to recommend solutions. Description of the state of knowledge: Student's t-test and ANOVA are parametric tests, and therefore some of the assumptions that need to be satisfied include normal distribution of the data and homogeneity of variances in groups. If the assumptions are violated, the original design of the test is impaired, and the test may then be compromised giving spurious results. A simple method to normalize the data and to stabilize the variance is to use transformations. If such approach fails, a good alternative to consider is a nonparametric test, such as Mann-Whitney, the Kruskal-Wallis or Wilcoxon signed-rank tests. Summary: Thorough verification of the parametric tests assumptions allows for correct selection of statistical tools, which is the basis of well-grounded statistical analysis. With a few simple rules, testing patterns in the data characteristic for the study of sports science comes down to a straightforward procedure.

Predicting Smoking Status Using Machine Learning Algorithms and Statistical Analysis

Directory of Open Access Journals (Sweden)

Charles Frank

2018-03-01

Full Text Available Smoking has been proven to negatively affect health in a multitude of ways. As of 2009, smoking has been considered the leading cause of preventable morbidity and mortality in the United States, continuing to plague the country’s overall health. This study aims to investigate the viability and effectiveness of some machine learning algorithms for predicting the smoking status of patients based on their blood tests and vital readings results. The analysis of this study is divided into two parts: In part 1, we use One-way ANOVA analysis with SAS tool to show the statistically significant difference in blood test readings between smokers and non-smokers. The results show that the difference in INR, which measures the effectiveness of anticoagulants, was significant in favor of non-smokers which further confirms the health risks associated with smoking. In part 2, we use five machine learning algorithms: Naïve Bayes, MLP, Logistic regression classifier, J48 and Decision Table to predict the smoking status of patients. To compare the effectiveness of these algorithms we use: Precision, Recall, F-measure and Accuracy measures. The results show that the Logistic algorithm outperformed the four other algorithms with Precision, Recall, F-Measure, and Accuracy of 83%, 83.4%, 83.2%, 83.44%, respectively.

Intelligent system for statistically significant expertise knowledge on the basis of the model of self-organizing nonequilibrium dissipative system

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E. A. Tatokchin

2017-01-01

Full Text Available Development of the modern educational technologies caused by broad introduction of comput-er testing and development of distant forms of education does necessary revision of methods of an examination of pupils. In work it was shown, need transition to mathematical criteria, exami-nations of knowledge which are deprived of subjectivity. In article the review of the problems arising at realization of this task and are offered approaches for its decision. The greatest atten-tion is paid to discussion of a problem of objective transformation of rated estimates of the ex-pert on to the scale estimates of the student. In general, the discussion this question is was con-cluded that the solution to this problem lies in the creation of specialized intellectual systems. The basis for constructing intelligent system laid the mathematical model of self-organizing nonequilibrium dissipative system, which is a group of students. This article assumes that the dissipative system is provided by the constant influx of new test items of the expert and non-equilibrium – individual psychological characteristics of students in the group. As a result, the system must self-organize themselves into stable patterns. This patern will allow for, relying on large amounts of data, get a statistically significant assessment of student. To justify the pro-posed approach in the work presents the data of the statistical analysis of the results of testing a large sample of students (> 90. Conclusions from this statistical analysis allowed to develop intelligent system statistically significant examination of student performance. It is based on data clustering algorithm (k-mean for the three key parameters. It is shown that this approach allows you to create of the dynamics and objective expertise evaluation.

The Importance of Integrating Clinical Relevance and Statistical Significance in the Assessment of Quality of Care--Illustrated Using the Swedish Stroke Register.

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Anita Lindmark

Full Text Available When profiling hospital performance, quality inicators are commonly evaluated through hospital-specific adjusted means with confidence intervals. When identifying deviations from a norm, large hospitals can have statistically significant results even for clinically irrelevant deviations while important deviations in small hospitals can remain undiscovered. We have used data from the Swedish Stroke Register (Riksstroke to illustrate the properties of a benchmarking method that integrates considerations of both clinical relevance and level of statistical significance.The performance measure used was case-mix adjusted risk of death or dependency in activities of daily living within 3 months after stroke. A hospital was labeled as having outlying performance if its case-mix adjusted risk exceeded a benchmark value with a specified statistical confidence level. The benchmark was expressed relative to the population risk and should reflect the clinically relevant deviation that is to be detected. A simulation study based on Riksstroke patient data from 2008-2009 was performed to investigate the effect of the choice of the statistical confidence level and benchmark value on the diagnostic properties of the method.Simulations were based on 18,309 patients in 76 hospitals. The widely used setting, comparing 95% confidence intervals to the national average, resulted in low sensitivity (0.252 and high specificity (0.991. There were large variations in sensitivity and specificity for different requirements of statistical confidence. Lowering statistical confidence improved sensitivity with a relatively smaller loss of specificity. Variations due to different benchmark values were smaller, especially for sensitivity. This allows the choice of a clinically relevant benchmark to be driven by clinical factors without major concerns about sufficiently reliable evidence.The study emphasizes the importance of combining clinical relevance and level of statistical

The Importance of Integrating Clinical Relevance and Statistical Significance in the Assessment of Quality of Care--Illustrated Using the Swedish Stroke Register.

Science.gov (United States)

Lindmark, Anita; van Rompaye, Bart; Goetghebeur, Els; Glader, Eva-Lotta; Eriksson, Marie

2016-01-01

When profiling hospital performance, quality inicators are commonly evaluated through hospital-specific adjusted means with confidence intervals. When identifying deviations from a norm, large hospitals can have statistically significant results even for clinically irrelevant deviations while important deviations in small hospitals can remain undiscovered. We have used data from the Swedish Stroke Register (Riksstroke) to illustrate the properties of a benchmarking method that integrates considerations of both clinical relevance and level of statistical significance. The performance measure used was case-mix adjusted risk of death or dependency in activities of daily living within 3 months after stroke. A hospital was labeled as having outlying performance if its case-mix adjusted risk exceeded a benchmark value with a specified statistical confidence level. The benchmark was expressed relative to the population risk and should reflect the clinically relevant deviation that is to be detected. A simulation study based on Riksstroke patient data from 2008-2009 was performed to investigate the effect of the choice of the statistical confidence level and benchmark value on the diagnostic properties of the method. Simulations were based on 18,309 patients in 76 hospitals. The widely used setting, comparing 95% confidence intervals to the national average, resulted in low sensitivity (0.252) and high specificity (0.991). There were large variations in sensitivity and specificity for different requirements of statistical confidence. Lowering statistical confidence improved sensitivity with a relatively smaller loss of specificity. Variations due to different benchmark values were smaller, especially for sensitivity. This allows the choice of a clinically relevant benchmark to be driven by clinical factors without major concerns about sufficiently reliable evidence. The study emphasizes the importance of combining clinical relevance and level of statistical confidence when

Estimates of statistical significance for comparison of individual positions in multiple sequence alignments

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Sadreyev Ruslan I

2004-08-01

Full Text Available Abstract Background Profile-based analysis of multiple sequence alignments (MSA allows for accurate comparison of protein families. Here, we address the problems of detecting statistically confident dissimilarities between (1 MSA position and a set of predicted residue frequencies, and (2 between two MSA positions. These problems are important for (i evaluation and optimization of methods predicting residue occurrence at protein positions; (ii detection of potentially misaligned regions in automatically produced alignments and their further refinement; and (iii detection of sites that determine functional or structural specificity in two related families. Results For problems (1 and (2, we propose analytical estimates of P-value and apply them to the detection of significant positional dissimilarities in various experimental situations. (a We compare structure-based predictions of residue propensities at a protein position to the actual residue frequencies in the MSA of homologs. (b We evaluate our method by the ability to detect erroneous position matches produced by an automatic sequence aligner. (c We compare MSA positions that correspond to residues aligned by automatic structure aligners. (d We compare MSA positions that are aligned by high-quality manual superposition of structures. Detected dissimilarities reveal shortcomings of the automatic methods for residue frequency prediction and alignment construction. For the high-quality structural alignments, the dissimilarities suggest sites of potential functional or structural importance. Conclusion The proposed computational method is of significant potential value for the analysis of protein families.

Optimization of friction welding by taguchi and ANOVA method on commercial aluminium tube to Al 2025 tube plate with backing block using an external tool

International Nuclear Information System (INIS)

Kanna, S.; Kumaraswamidhs, L. A.; Kumaran, S. Senthil

2016-01-01

The aim of the present work is to optimize the Friction welding of tube to tube plate using an external tool (FWTPET) with clearance fit of commercial aluminum tube to Al 2025 tube plate using an external tool. Conventional frictional welding is suitable to weld only symmetrical joints either tube to tube or rod to rod but in this research with the help of external tool, the welding has been done by unsymmetrical shape of tube to tube plate also. In this investigation, the various welding parameters such as tool rotating speed (rpm), projection of tube (mm) and depth of cut (mm) are determined according to the Taguchi L9 orthogonal array. The two conditions were considered in this process to examine this experiment; where condition 1 is flat plate with plain tube Without holes [WOH] on the circumference of the surface and condition 2 is flat plate with plane tube has holes on its circumference of the surface With holes [WH]. Taguchi L9 orthogonal array was utilized to find the most significant control factors which will yield better joint strength. Besides, the most influential process parameter has been determined using statistical Analysis of variance (ANOVA). Finally, the comparison of each result has been done for conditions by means percentage of contribution and regression analysis. The general regression equation is formulated and better strength is obtained and it is validated by means of confirmation test. It was observed that value of optimal welded joint strength for both tube without holes and tube with holes are to be 319.485 MPa and 264.825 MPa, respectively.

Optimization of friction welding by taguchi and ANOVA method on commercial aluminium tube to Al 2025 tube plate with backing block using an external tool

Energy Technology Data Exchange (ETDEWEB)

Kanna, S.; Kumaraswamidhs, L. A. [Indian Institute of Technology, Dhanbad (India); Kumaran, S. Senthil [RVS School of Engineering and Technology, Dindigul (India)

2016-05-15

The aim of the present work is to optimize the Friction welding of tube to tube plate using an external tool (FWTPET) with clearance fit of commercial aluminum tube to Al 2025 tube plate using an external tool. Conventional frictional welding is suitable to weld only symmetrical joints either tube to tube or rod to rod but in this research with the help of external tool, the welding has been done by unsymmetrical shape of tube to tube plate also. In this investigation, the various welding parameters such as tool rotating speed (rpm), projection of tube (mm) and depth of cut (mm) are determined according to the Taguchi L9 orthogonal array. The two conditions were considered in this process to examine this experiment; where condition 1 is flat plate with plain tube Without holes [WOH] on the circumference of the surface and condition 2 is flat plate with plane tube has holes on its circumference of the surface With holes [WH]. Taguchi L9 orthogonal array was utilized to find the most significant control factors which will yield better joint strength. Besides, the most influential process parameter has been determined using statistical Analysis of variance (ANOVA). Finally, the comparison of each result has been done for conditions by means percentage of contribution and regression analysis. The general regression equation is formulated and better strength is obtained and it is validated by means of confirmation test. It was observed that value of optimal welded joint strength for both tube without holes and tube with holes are to be 319.485 MPa and 264.825 MPa, respectively.

Test the Overall Significance of p-values by Using Joint Tail Probability of Ordered p-values as Test Statistic

NARCIS (Netherlands)

Fang, Yongxiang; Wit, Ernst

2008-01-01

Fisher’s combined probability test is the most commonly used method to test the overall significance of a set independent p-values. However, it is very obviously that Fisher’s statistic is more sensitive to smaller p-values than to larger p-value and a small p-value may overrule the other p-values

Statistics of Data Fitting: Flaws and Fixes of Polynomial Analysis of Channeled Spectra

Science.gov (United States)

Karstens, William; Smith, David

2013-03-01

Starting from general statistical principles, we have critically examined Baumeister's procedure* for determining the refractive index of thin films from channeled spectra. Briefly, the method assumes that the index and interference fringe order may be approximated by polynomials quadratic and cubic in photon energy, respectively. The coefficients of the polynomials are related by differentiation, which is equivalent to comparing energy differences between fringes. However, we find that when the fringe order is calculated from the published IR index for silicon* and then analyzed with Baumeister's procedure, the results do not reproduce the original index. This problem has been traced to 1. Use of unphysical powers in the polynomials (e.g., time-reversal invariance requires that the index is an even function of photon energy), and 2. Use of insufficient terms of the correct parity. Exclusion of unphysical terms and addition of quartic and quintic terms to the index and order polynomials yields significantly better fits with fewer parameters. This represents a specific example of using statistics to determine if the assumed fitting model adequately captures the physics contained in experimental data. The use of analysis of variance (ANOVA) and the Durbin-Watson statistic to test criteria for the validity of least-squares fitting will be discussed. *D.F. Edwards and E. Ochoa, Appl. Opt. 19, 4130 (1980). Supported in part by the US Department of Energy, Office of Nuclear Physics under contract DE-AC02-06CH11357.

Different histopathological subtypes of Hodgkin lymphoma show significantly different levels of FDG uptake

DEFF Research Database (Denmark)

Hutchings, Martin; Loft, Annika; Hansen, Mads

2006-01-01

) patients, 20.8 g/ml in 11 mixed cellularity (MC) patients, and 19.5 g/ml in four patients with unclassified classical HL (CHL-NOS), (ANOVA, p = 0.011). Out of 780 sites (600 lymph node regions plus 180 organs), 208 sites were found to be affected with HL. Mean SUV(max) was 8.3 g/ml in the 12 sites with NLP......, 11.2 g/ml in the 147 sites affected with NS, 14.6 g/ml in the 36 sites with MC, and 13.1 g/ml in the 13 sites with CHL-NOS (ANOVA, p = 0.002). There is a significant difference in FDG/glucose uptake between the different histopathological subtypes of HL....

Statistical analysis of real ILI (In-Line Inspection) data: implications, inferences and lessons learned

Energy Technology Data Exchange (ETDEWEB)

Timashev, Svyatoslav A.; Bushinskaya, Anna V. [Russian Academy of Sciences, Ekaterinburg (Russian Federation). Ural Branch. Sciences and Engineering Center ' Reliability and Safety of Large Systems and Machines'

2009-07-01

The paper discusses current possibilities and drawbacks of in-line inspection (ILI) in sizing defects in oil and gas pipelines. A methodology based on analysis of variances (ANOVA) is presented that extracts maximum possible information from the ILI measurements of defects and subsequent verification results. This full statistical analysis (FSA) methodology was extensively tested by using the Monte Carlo simulation method. It was then applied to analyze the content of sections 7, 9 and appendix E of the API 1163 RP Standard. (author)

Statistical Optimization of Synthesis of Manganese Carbonates Nanoparticles by Precipitation Methods

International Nuclear Information System (INIS)

Javidan, A.; Rahimi-Nasrabadi, M.; Davoudi, A.A.

2011-01-01

In this study, an orthogonal array design (OAD), OA9, was employed as a statistical experimental method for the controllable, simple and fast synthesis of manganese carbonate nanoparticle. Ultrafine manganese carbonate nanoparticles were synthesized by a precipitation method involving the addition of manganese ion solution to the carbonate reagent. The effects of reaction conditions, for example, manganese and carbonate concentrations, flow rate of reagent addition and temperature, on the diameter of the synthesized manganese carbonate nanoparticle were investigated. The effects of these factors on the width of the manganese carbonate nanoparticle were quantitatively evaluated by the analysis of variance (ANOVA). The results showed that manganese carbonate nanoparticle can be synthesized by controlling the manganese concentration, flow rate and temperature. Finally, the optimum conditions for the synthesis of manganese carbonate nanoparticle by this simple and fast method were proposed. The results of ANOVA showed that 0.001 mol/ L manganese ion and carbonate reagents concentrations, 2.5 mL/ min flow rate for the addition of the manganese reagent to the carbonate solution and 0 degree Celsius temperature are the optimum conditions for producing manganese carbonate nanoparticle with 75 ± 25 nm width. (author)

Statistical determination of significant curved I-girder bridge seismic response parameters

Science.gov (United States)

Seo, Junwon

2013-06-01

Curved steel bridges are commonly used at interchanges in transportation networks and more of these structures continue to be designed and built in the United States. Though the use of these bridges continues to increase in locations that experience high seismicity, the effects of curvature and other parameters on their seismic behaviors have been neglected in current risk assessment tools. These tools can evaluate the seismic vulnerability of a transportation network using fragility curves. One critical component of fragility curve development for curved steel bridges is the completion of sensitivity analyses that help identify influential parameters related to their seismic response. In this study, an accessible inventory of existing curved steel girder bridges located primarily in the Mid-Atlantic United States (MAUS) was used to establish statistical characteristics used as inputs for a seismic sensitivity study. Critical seismic response quantities were captured using 3D nonlinear finite element models. Influential parameters from these quantities were identified using statistical tools that incorporate experimental Plackett-Burman Design (PBD), which included Pareto optimal plots and prediction profiler techniques. The findings revealed that the potential variation in the influential parameters included number of spans, radius of curvature, maximum span length, girder spacing, and cross-frame spacing. These parameters showed varying levels of influence on the critical bridge response.

Statistical methods for detecting and comparing periodic data and their application to the nycthemeral rhythm of bodily harm: A population based study

LENUS (Irish Health Repository)

Stroebel, Armin M

2010-11-08

Abstract Background Animals, including humans, exhibit a variety of biological rhythms. This article describes a method for the detection and simultaneous comparison of multiple nycthemeral rhythms. Methods A statistical method for detecting periodic patterns in time-related data via harmonic regression is described. The method is particularly capable of detecting nycthemeral rhythms in medical data. Additionally a method for simultaneously comparing two or more periodic patterns is described, which derives from the analysis of variance (ANOVA). This method statistically confirms or rejects equality of periodic patterns. Mathematical descriptions of the detecting method and the comparing method are displayed. Results Nycthemeral rhythms of incidents of bodily harm in Middle Franconia are analyzed in order to demonstrate both methods. Every day of the week showed a significant nycthemeral rhythm of bodily harm. These seven patterns of the week were compared to each other revealing only two different nycthemeral rhythms, one for Friday and Saturday and one for the other weekdays.

Quantile regression for the statistical analysis of immunological data with many non-detects.

Science.gov (United States)

Eilers, Paul H C; Röder, Esther; Savelkoul, Huub F J; van Wijk, Roy Gerth

2012-07-07

Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical techniques currently available for the analysis of datasets with non-detects can only be used if a small percentage of the data are non-detects. Quantile regression, a generalization of percentiles to regression models, models the median or higher percentiles and tolerates very high numbers of non-detects. We present a non-technical introduction and illustrate it with an implementation to real data from a clinical trial. We show that by using quantile regression, groups can be compared and that meaningful linear trends can be computed, even if more than half of the data consists of non-detects. Quantile regression is a valuable addition to the statistical methods that can be used for the analysis of immunological datasets with non-detects.

Absolute variation of the mechanical characteristics of halloysite reinforced polyurethane nanocomposites complemented by Taguchi and ANOVA approaches

Directory of Open Access Journals (Sweden)

Tayser Sumer Gaaz

Full Text Available The variation of the results of the mechanical properties of halloysite nanotubes (HNTs reinforced thermoplastic polyurethane (TPU at different HNTs loadings was implemented as a tool for analysis. The preparation of HNTs-TPU nanocomposites was performed under four controlled parameters of mixing temperature, mixing speed, mixing time, and HNTs loading at three levels each to satisfy Taguchi method orthogonal array L9 aiming to optimize these parameters for the best measurements of tensile strength, Young’s modulus, and tensile strain (known as responses. The maximum variation of the experimental results for each response was determined and analysed based on the optimized results predicted by Taguchi method and ANOVA. It was found that the maximum absolute variations of the three mentioned responses are 69%, 352%, and 126%, respectively. The analysis has shown that the preparation of the optimized tensile strength requires 1 wt.% HNTs loading (excluding 2 wt.% and 3 wt.%, mixing temperature of 190 °C (excluding 200 °C and 210 °C, and mixing speed of 30 rpm (excluding 40 rpm and 50 rpm. In addition, the analysis has determined that the mixing time at 20 min has no effect on the preparation. The mentioned analysis was fortified by ANOVA, images of FESEM, and DSC results. Seemingly, the agglomeration and distribution of HNTs in the nanocomposite play an important role in the process. The outcome of the analysis could be considered as a very important step towards the reliability of Taguchi method. Keywords: Nanocomposite, Design-of-experiment, Taguchi optimization method, Mechanical properties

Wear behavior of AA 5083/SiC nano-particle metal matrix composite: Statistical analysis

Science.gov (United States)

Hussain Idrisi, Amir; Ismail Mourad, Abdel-Hamid; Thekkuden, Dinu Thomas; Christy, John Victor

2018-03-01

This paper reports study on statistical analysis of the wear characteristics of AA5083/SiC nanocomposite. The aluminum matrix composites with different wt % (0%, 1% and 2%) of SiC nanoparticles were fabricated by using stir casting route. The developed composites were used in the manufacturing of spur gears on which the study was conducted. A specially designed test rig was used in testing the wear performance of the gears. The wear was investigated under different conditions of applied load (10N, 20N, and 30N) and operation time (30 mins, 60 mins, 90 mins, and 120mins). The analysis carried out at room temperature under constant speed of 1450 rpm. The wear parameters were optimized by using Taguchi’s method. During this statistical approach, L27 Orthogonal array was selected for the analysis of output. Furthermore, analysis of variance (ANOVA) was used to investigate the influence of applied load, operation time and SiC wt. % on wear behaviour. The wear resistance was analyzed by selecting “smaller is better” characteristics as the objective of the model. From this research, it is observed that experiment time and SiC wt % have the most significant effect on the wear performance followed by the applied load.

The influence of speed abilities and technical skills in early adolescence on adult success in soccer: A long-term prospective analysis using ANOVA and SEM approaches

Science.gov (United States)

2017-01-01

Several talent development programs in youth soccer have implemented motor diagnostics measuring performance factors. However, the predictive value of such tests for adult success is a controversial topic in talent research. This prospective cohort study evaluated the long-term predictive value of 1) motor tests and 2) players’ speed abilities (SA) and technical skills (TS) in early adolescence. The sample consisted of 14,178 U12 players from the German talent development program. Five tests (sprint, agility, dribbling, ball control, shooting) were conducted and players’ height, weight as well as relative age were assessed at nationwide diagnostics between 2004 and 2006. In the 2014/15 season, the players were then categorized as professional (n = 89), semi-professional (n = 913), or non-professional players (n = 13,176), indicating their adult performance level (APL). The motor tests’ prognostic relevance was determined using ANOVAs. Players’ future success was predicted by a logistic regression threshold model. This structural equation model comprised a measurement model with the motor tests and two correlated latent factors, SA and TS, with simultaneous consideration for the manifest covariates height, weight and relative age. Each motor predictor and anthropometric characteristic discriminated significantly between the APL (p < .001; η2 ≤ .02). The threshold model significantly predicted the APL (R2 = 24.8%), and in early adolescence the factor TS (p < .001) seems to have a stronger effect on adult performance than SA (p < .05). Both approaches (ANOVA, SEM) verified the diagnostics’ predictive validity over a long-term period (≈ 9 years). However, because of the limited effect sizes, the motor tests’ prognostic relevance remains ambiguous. A challenge for future research lies in the integration of different (e.g., person-oriented or multilevel) multivariate approaches that expand beyond the “traditional” topic of single tests’ predictive

Statistically significant dependence of the Xaa-Pro peptide bond conformation on secondary structure and amino acid sequence

Directory of Open Access Journals (Sweden)

Leitner Dietmar

2005-04-01

Full Text Available Abstract Background A reliable prediction of the Xaa-Pro peptide bond conformation would be a useful tool for many protein structure calculation methods. We have analyzed the Protein Data Bank and show that the combined use of sequential and structural information has a predictive value for the assessment of the cis versus trans peptide bond conformation of Xaa-Pro within proteins. For the analysis of the data sets different statistical methods such as the calculation of the Chou-Fasman parameters and occurrence matrices were used. Furthermore we analyzed the relationship between the relative solvent accessibility and the relative occurrence of prolines in the cis and in the trans conformation. Results One of the main results of the statistical investigations is the ranking of the secondary structure and sequence information with respect to the prediction of the Xaa-Pro peptide bond conformation. We observed a significant impact of secondary structure information on the occurrence of the Xaa-Pro peptide bond conformation, while the sequence information of amino acids neighboring proline is of little predictive value for the conformation of this bond. Conclusion In this work, we present an extensive analysis of the occurrence of the cis and trans proline conformation in proteins. Based on the data set, we derived patterns and rules for a possible prediction of the proline conformation. Upon adoption of the Chou-Fasman parameters, we are able to derive statistically relevant correlations between the secondary structure of amino acid fragments and the Xaa-Pro peptide bond conformation.

High-intensity interval training (swimming) significantly improves the adverse metabolism and comorbidities in diet-induced obese mice.

Science.gov (United States)

Motta, Victor F; Aguila, Marcia B; Mandarim-DE-Lacerda, Carlos A

2016-05-01

Controlling obesity and other comorbidities in the population is a challenge in modern society. High-intensity interval training (HIIT) combines short periods of high-intensity exercise with long recovery periods or a low-intensity exercise. The aim was to assess the impact of HIIT in the context of diet-induced obesity in the animal model. C57BL/6 mice were fed one of the two diets: standard chow (lean group [LE]) or a high-fat diet (obese group [OB]). After twelve weeks, the animals were divided into non-trained groups (LE-NT and OB-NT) and trained groups (LE-T and OB-T), and began an exercise protocol. For biochemical analysis of inflammatory and lipid profile, we used a colorimetric enzymatic method and an automatic spectrophotometer. One-way ANOVA was used for statistical analysis of the experimental groups with Holm-Sidak post-hoc Test. Two-way ANOVA analyzed the interactions between diet and HIIT protocol. HIIT leads to significant reductions in body mass, blood glucose, glucose tolerance and hepatic lipid profile in T-groups compared to NT-groups. HIIT was able to reduce plasma levels of inflammatory cytokines. Additionally, HIIT improves the insulin immunodensity in the islets, reduces the adiposity and the hepatic steatosis in the T-groups. HIIT improves beta-oxidation and peroxisome proliferator-activated receptor (PPAR)-alpha and reduces lipogenesis and PPAR-gamma levels in the liver. In skeletal muscle, HIIT improves PPAR-alpha and glucose transporter-4 and reduces PPAR-gamma levels. HIIT leads to attenuate the adverse effects caused by a chronic ingestion of a high-fat diet.

CONFIDENCE LEVELS AND/VS. STATISTICAL HYPOTHESIS TESTING IN STATISTICAL ANALYSIS. CASE STUDY

Directory of Open Access Journals (Sweden)

ILEANA BRUDIU

2009-05-01

Full Text Available Estimated parameters with confidence intervals and testing statistical assumptions used in statistical analysis to obtain conclusions on research from a sample extracted from the population. Paper to the case study presented aims to highlight the importance of volume of sample taken in the study and how this reflects on the results obtained when using confidence intervals and testing for pregnant. If statistical testing hypotheses not only give an answer "yes" or "no" to some questions of statistical estimation using statistical confidence intervals provides more information than a test statistic, show high degree of uncertainty arising from small samples and findings build in the "marginally significant" or "almost significant (p very close to 0.05.

CFAssay: statistical analysis of the colony formation assay

International Nuclear Information System (INIS)

Braselmann, Herbert; Michna, Agata; Heß, Julia; Unger, Kristian

2015-01-01

Colony formation assay is the gold standard to determine cell reproductive death after treatment with ionizing radiation, applied for different cell lines or in combination with other treatment modalities. Associated linear-quadratic cell survival curves can be calculated with different methods. For easy code exchange and methodological standardisation among collaborating laboratories a software package CFAssay for R (R Core Team, R: A Language and Environment for Statistical Computing, 2014) was established to perform thorough statistical analysis of linear-quadratic cell survival curves after treatment with ionizing radiation and of two-way designs of experiments with chemical treatments only. CFAssay offers maximum likelihood and related methods by default and the least squares or weighted least squares method can be optionally chosen. A test for comparision of cell survival curves and an ANOVA test for experimental two-way designs are provided. For the two presented examples estimated parameters do not differ much between maximum-likelihood and least squares. However the dispersion parameter of the quasi-likelihood method is much more sensitive for statistical variation in the data than the multiple R 2 coefficient of determination from the least squares method. The dispersion parameter for goodness of fit and different plot functions in CFAssay help to evaluate experimental data quality. As open source software interlaboratory code sharing between users is facilitated

Statistical inference for classification of RRIM clone series using near IR reflectance properties

Science.gov (United States)

Ismail, Faridatul Aima; Madzhi, Nina Korlina; Hashim, Hadzli; Abdullah, Noor Ezan; Khairuzzaman, Noor Aishah; Azmi, Azrie Faris Mohd; Sampian, Ahmad Faiz Mohd; Harun, Muhammad Hafiz

2015-08-01

RRIM clone is a rubber breeding series produced by RRIM (Rubber Research Institute of Malaysia) through "rubber breeding program" to improve latex yield and producing clones attractive to farmers. The objective of this work is to analyse measurement of optical sensing device on latex of selected clone series. The device using transmitting NIR properties and its reflectance is converted in terms of voltage. The obtained reflectance index value via voltage was analyzed using statistical technique in order to find out the discrimination among the clones. From the statistical results using error plots and one-way ANOVA test, there is an overwhelming evidence showing discrimination of RRIM 2002, RRIM 2007 and RRIM 3001 clone series with p value = 0.000. RRIM 2008 cannot be discriminated with RRIM 2014; however both of these groups are distinct from the other clones.

Encoding Dissimilarity Data for Statistical Model Building.

Science.gov (United States)

Wahba, Grace

2010-12-01

We summarize, review and comment upon three papers which discuss the use of discrete, noisy, incomplete, scattered pairwise dissimilarity data in statistical model building. Convex cone optimization codes are used to embed the objects into a Euclidean space which respects the dissimilarity information while controlling the dimension of the space. A "newbie" algorithm is provided for embedding new objects into this space. This allows the dissimilarity information to be incorporated into a Smoothing Spline ANOVA penalized likelihood model, a Support Vector Machine, or any model that will admit Reproducing Kernel Hilbert Space components, for nonparametric regression, supervised learning, or semi-supervised learning. Future work and open questions are discussed. The papers are: F. Lu, S. Keles, S. Wright and G. Wahba 2005. A framework for kernel regularization with application to protein clustering. Proceedings of the National Academy of Sciences 102, 12332-1233.G. Corrada Bravo, G. Wahba, K. Lee, B. Klein, R. Klein and S. Iyengar 2009. Examining the relative influence of familial, genetic and environmental covariate information in flexible risk models. Proceedings of the National Academy of Sciences 106, 8128-8133F. Lu, Y. Lin and G. Wahba. Robust manifold unfolding with kernel regularization. TR 1008, Department of Statistics, University of Wisconsin-Madison.

Color stability and degree of cure of direct composite restoratives after accelerated aging.

Science.gov (United States)

Sarafianou, Aspasia; Iosifidou, Soultana; Papadopoulos, Triantafillos; Eliades, George

2007-01-01

This study evaluated the color changes and amount of remaining C = C bonds (%RDB) in three dental composites after hydrothermal- and photoaging. The materials tested were Estelite sigma, Filtek Supreme and Tetric Ceram. Specimens were fabricated from each material and subjected to L* a* b* colorimetry and FTIR spectroscopy before and after aging. Statistical evaluation of the deltaL,* deltaa,* deltab,* deltaE and %deltaRDB data was performed by one-way ANOVA and Tukey's test. The %RDB data before and after aging were statistically analyzed using two-way ANOVA and Student-Newman-Keuls test. In all cases an alpha = 0.05 significance level was used. No statistically significant differences were found in deltaL*, deltaa*, deltaE and %deltaRDB among the materials tested. Tetric Ceram demonstrated a significant difference in deltab*. All the materials showed visually perceptible (deltaE >1) but clinically acceptable values (deltaE statistically significant differences in %RDB were noticed before and after aging (p statistically significantly different among all the groups tested. No correlation was found between deltaE and %deltaRDB.

Statistical analysis of surface roughness of machined graphite by means of CNC milling

Directory of Open Access Journals (Sweden)

Orquídea Sánchez López

2016-09-01

Full Text Available The aim of this research is to analyze the influence of cutting speed, feed rate and cutting depth on the surface finish of grade GSP-70 graphite specimens for use in electrical discharge machining (EDM for material removal by means of Computer Numerical Control (CNC milling with low-speed machining (LSM. A two-level factorial design for each of the three established factors was used for the statistical analysis. The analysis of variance (ANOVA indicates that cutting speed and feed rate are the two most significant factors with regard to the roughness obtained with grade GSP-70 graphite by means of CNC milling. A second order regression analysis was also conducted to estimate the roughness average (Ra in terms of the cutting speed, feed rate and cutting depth. Finally, the comparison between predicted roughness by means of a second order regression model and the roughness obtained by machined specimens considering the combinations of low and high levels of roughness is also presented.

Tips and Tricks for Successful Application of Statistical Methods to Biological Data.

Science.gov (United States)

Schlenker, Evelyn

2016-01-01

This chapter discusses experimental design and use of statistics to describe characteristics of data (descriptive statistics) and inferential statistics that test the hypothesis posed by the investigator. Inferential statistics, based on probability distributions, depend upon the type and distribution of the data. For data that are continuous, randomly and independently selected, as well as normally distributed more powerful parametric tests such as Student's t test and analysis of variance (ANOVA) can be used. For non-normally distributed or skewed data, transformation of the data (using logarithms) may normalize the data allowing use of parametric tests. Alternatively, with skewed data nonparametric tests can be utilized, some of which rely on data that are ranked prior to statistical analysis. Experimental designs and analyses need to balance between committing type 1 errors (false positives) and type 2 errors (false negatives). For a variety of clinical studies that determine risk or benefit, relative risk ratios (random clinical trials and cohort studies) or odds ratios (case-control studies) are utilized. Although both use 2 × 2 tables, their premise and calculations differ. Finally, special statistical methods are applied to microarray and proteomics data, since the large number of genes or proteins evaluated increase the likelihood of false discoveries. Additional studies in separate samples are used to verify microarray and proteomic data. Examples in this chapter and references are available to help continued investigation of experimental designs and appropriate data analysis.

Statistical analysis of natural radiation levels inside the UNICAMP campus through the use of Geiger-Muller counter; Analise estatistica dos niveis de radiacao natural dentro da UNICAMP atraves do uso de contador Geiger-Muller

Energy Technology Data Exchange (ETDEWEB)

Fontolan, Juliana A.; Biral, Antonio Renato P., E-mail: fontolanjuliana@gmail.com.br, E-mail: biral@ceb.unicamp.br [Hospital das Clinicas (CEB/UNICAMP), Campinas, SP (Brazil). Centro de Engenharia Biomedica

2013-07-01

It is known that the distribution at time intervals of random and unrelated events leads to the Poisson distribution . This work aims to study the distribution in time intervals of events resulting from radioactive decay of atoms present in the UNICAMP where activities involving the use of ionizing radiation are performed environments . The proposal is that the distribution surveys at intervals of these events in different locations of the university are carried out through the use of a Geiger-Mueller tube . In a next step , the evaluation of distributions obtained by using non- parametric statistics (Chi- square and Kolmogorov Smirnoff) will be taken . For analyzes involving correlations we intend to use the ANOVA (Analysis of Variance) statistical tool . Measured in six different places within the Campinas , with the use of Geiger- Muller its count mode and a time window of 20 seconds was performed . Through statistical tools chi- square and Kolmogorov Smirnoff tests, using the EXCEL program , it was observed that the distributions actually refer to a Poisson distribution. Finally, the next step is to perform analyzes involving correlations using the statistical tool ANOVA.

Facilitating the Transition from Bright to Dim Environments

Science.gov (United States)

2016-03-04

For the parametric data, a multivariate ANOVA was used in determining the systematic presence of any statistically significant performance differences...performed. All significance levels were p < 0.05, and statistical analyses were performed with the Statistical Package for Social Sciences ( SPSS ...1950. Age changes in rate and level of visual dark adaptation. Journal of Applied Physiology, 2, 407–411. Field, A. 2009. Discovering statistics

Further statistical analysis for genome-wide expression evolution in primate brain/liver/fibroblast tissue

Directory of Open Access Journals (Sweden)

Gu Jianying

2004-05-01

Full Text Available Abstract In spite of only a 1-2 per cent genomic DNA sequence difference, humans and chimpanzees differ considerably in behaviour and cognition. Affymetrix microarray technology provides a novel approach to addressing a long-term debate on whether the difference between humans and chimpanzees results from the alteration of gene expressions. Here, we used several statistical methods (distance method, two-sample t-tests, regularised t-tests, ANOVA and bootstrapping to detect the differential expression pattern between humans and great apes. Our analysis shows that the pattern we observed before is robust against various statistical methods; that is, the pronounced expression changes occurred on the human lineage after the split from chimpanzees, and that the dramatic brain expression alterations in humans may be mainly driven by a set of genes with increased expression (up-regulated rather than decreased expression (down-regulated.

Determining coding CpG islands by identifying regions significant for pattern statistics on Markov chains.

Science.gov (United States)

Singer, Meromit; Engström, Alexander; Schönhuth, Alexander; Pachter, Lior

2011-09-23

Recent experimental and computational work confirms that CpGs can be unmethylated inside coding exons, thereby showing that codons may be subjected to both genomic and epigenomic constraint. It is therefore of interest to identify coding CpG islands (CCGIs) that are regions inside exons enriched for CpGs. The difficulty in identifying such islands is that coding exons exhibit sequence biases determined by codon usage and constraints that must be taken into account. We present a method for finding CCGIs that showcases a novel approach we have developed for identifying regions of interest that are significant (with respect to a Markov chain) for the counts of any pattern. Our method begins with the exact computation of tail probabilities for the number of CpGs in all regions contained in coding exons, and then applies a greedy algorithm for selecting islands from among the regions. We show that the greedy algorithm provably optimizes a biologically motivated criterion for selecting islands while controlling the false discovery rate. We applied this approach to the human genome (hg18) and annotated CpG islands in coding exons. The statistical criterion we apply to evaluating islands reduces the number of false positives in existing annotations, while our approach to defining islands reveals significant numbers of undiscovered CCGIs in coding exons. Many of these appear to be examples of functional epigenetic specialization in coding exons.

Statistical comparison of spectral and biochemical measurements on an example of Norway spruce stands in the Ore Mountains, Czech Republic

Directory of Open Access Journals (Sweden)

Markéta Potůčková

2016-07-01

Full Text Available The physiological status of vegetation and changes thereto can be monitored by means of biochemical analysis of collected samples as well as by means of spectroscopic measurements either on the leaf level, using field (or laboratory spectroradiometers or on the canopy level, applying hyperspectral airborne or spaceborne image data. The presented study focuses on the statistical comparison and ascertainment of relations between three datasets collected from selected Norway spruce forest stands in the Ore Mountains, Czechia. The data sets comprise i photosynthetic pigments (chlorophylls, carotenoids and water content of 495 samples collected from 55 trees from three different vertical levels and the first three needle age classes, ii the spectral reflectance of the same samples measured with an ASD Field Spec 4 Wide-Res spectroradiometer equipped with a plant contact probe, iii an airborne hyperspecral image acquired with an Apex sensor. The datasets cover two localities in the Ore Mountains that were affected differently by acid deposits in the 1970s and 1980s. A one-way analysis of variance (ANOVA, Tukey’s honest significance test, hot spot analysis and linear regression were applied either on the original measurements (the content of leaf compounds and reflectance spectra or derived values, i.e., selected spectral indices. The results revealed a generally low correlation between the photosynthetic pigments, water content and spectral measurement. The results of the ANOVA showed significant differences between sites (model areas only in the case of the leaf compound dataset. Differences between the stands on various levels of significance exist in all three datasets and are explained in detail. The study also proved that the vertical gradient of the biochemical and biophysical parameters in the canopy play a role when the optical properties of the forest stands are modelled.

Combination of statistical approaches for analysis of 2-DE data gives complementary results

DEFF Research Database (Denmark)

Grove, Harald; Jørgensen, Bo; Jessen, Flemming

2008-01-01

Five methods for finding significant changes in proteome data have been used to analyze a two-dimensional gel electrophoresis data set. We used both univariate (ANOVA) and multivariate (Partial Least Squares with jackknife, Cross Model Validation, Power-PLS and CovProc) methods. The gels were taken...

Omega-3 fatty acid therapy dose-dependently and significantly decreased triglycerides and improved flow-mediated dilation, however, did not significantly improve insulin sensitivity in patients with hypertriglyceridemia.

Science.gov (United States)

Oh, Pyung Chun; Koh, Kwang Kon; Sakuma, Ichiro; Lim, Soo; Lee, Yonghee; Lee, Seungik; Lee, Kyounghoon; Han, Seung Hwan; Shin, Eak Kyun

2014-10-20

Experimental studies demonstrate that higher intake of omega-3 fatty acids (n-3 FA) improves insulin sensitivity, however, we reported that n-3 FA 2g therapy, most commonly used dosage did not significantly improve insulin sensitivity despite reducing triglycerides by 21% in patients. Therefore, we investigated the effects of different dosages of n-3 FA in patients with hypertriglyceridemia. This was a randomized, single-blind, placebo-controlled, parallel study. Age, sex, and body mass index were matched among groups. All patients were recommended to maintain a low fat diet. Forty-four patients (about 18 had metabolic syndrome/type 2 diabetes mellitus) in each group were given placebo, n-3 FA 1 (O1), 2 (O2), or 4 g (O4), respectively daily for 2 months. n-3 FA therapy dose-dependently and significantly decreased triglycerides and triglycerides/HDL cholesterol and improved flow-mediated dilation, compared with placebo (by ANOVA). However, each n-3 FA therapy did not significantly decrease high-sensitivity C-reactive protein and fibrinogen, compared with placebo. O1 significantly increased insulin levels and decreased insulin sensitivity (determined by QUICKI) and O2 significantly decreased plasma adiponectin levels relative to baseline measurements. Of note, when compared with placebo, each n-3 FA therapy did not significantly change insulin, glucose, adiponectin, glycated hemoglobin levels and insulin sensitivity (by ANOVA). We observed similar results in a subgroup of patients with the metabolic syndrome. n-3 FA therapy dose-dependently and significantly decreased triglycerides and improved flow-mediated dilation. Nonetheless, n-3 FA therapy did not significantly improve acute-phase reactants and insulin sensitivity in patients with hypertriglyceridemia, regardless of dosages. Copyright © 2014. Published by Elsevier Ireland Ltd.

Cetirizine release from cyclodextrin formulated compressed chewing gum

DEFF Research Database (Denmark)

Stojanov, Mladen; Larsen, Kim Lambertsen

2012-01-01

release patterns, but with variations in the total amount released. Chewing gum formulated with cetirizine alone, demonstrated a release of 75% after 8 min of chewing. The presence of CDs resulted in increased cetirizine release. The analysis of variance (ANOVA) demonstrated that parameters with the most...... the statistical analysis (ANOVA) demonstrated significance in the release (P

Analysis of tribological behaviour of zirconia reinforced Al-SiC hybrid composites using statistical and artificial neural network technique

Science.gov (United States)

Arif, Sajjad; Tanwir Alam, Md; Ansari, Akhter H.; Bilal Naim Shaikh, Mohd; Arif Siddiqui, M.

2018-05-01

The tribological performance of aluminium hybrid composites reinforced with micro SiC (5 wt%) and nano zirconia (0, 3, 6 and 9 wt%) fabricated through powder metallurgy technique were investigated using statistical and artificial neural network (ANN) approach. The influence of zirconia reinforcement, sliding distance and applied load were analyzed with test based on full factorial design of experiments. Analysis of variance (ANOVA) was used to evaluate the percentage contribution of each process parameters on wear loss. ANOVA approach suggested that wear loss be mainly influenced by sliding distance followed by zirconia reinforcement and applied load. Further, a feed forward back propagation neural network was applied on input/output date for predicting and analyzing the wear behaviour of fabricated composite. A very close correlation between experimental and ANN output were achieved by implementing the model. Finally, ANN model was effectively used to find the influence of various control factors on wear behaviour of hybrid composites.

Statistical modelling of transcript profiles of differentially regulated genes

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Sergeant Martin J

2008-07-01

Full Text Available Abstract Background The vast quantities of gene expression profiling data produced in microarray studies, and the more precise quantitative PCR, are often not statistically analysed to their full potential. Previous studies have summarised gene expression profiles using simple descriptive statistics, basic analysis of variance (ANOVA and the clustering of genes based on simple models fitted to their expression profiles over time. We report the novel application of statistical non-linear regression modelling techniques to describe the shapes of expression profiles for the fungus Agaricus bisporus, quantified by PCR, and for E. coli and Rattus norvegicus, using microarray technology. The use of parametric non-linear regression models provides a more precise description of expression profiles, reducing the "noise" of the raw data to produce a clear "signal" given by the fitted curve, and describing each profile with a small number of biologically interpretable parameters. This approach then allows the direct comparison and clustering of the shapes of response patterns between genes and potentially enables a greater exploration and interpretation of the biological processes driving gene expression. Results Quantitative reverse transcriptase PCR-derived time-course data of genes were modelled. "Split-line" or "broken-stick" regression identified the initial time of gene up-regulation, enabling the classification of genes into those with primary and secondary responses. Five-day profiles were modelled using the biologically-oriented, critical exponential curve, y(t = A + (B + CtRt + ε. This non-linear regression approach allowed the expression patterns for different genes to be compared in terms of curve shape, time of maximal transcript level and the decline and asymptotic response levels. Three distinct regulatory patterns were identified for the five genes studied. Applying the regression modelling approach to microarray-derived time course data

Statistical significance approximation in local trend analysis of high-throughput time-series data using the theory of Markov chains.

Science.gov (United States)

Xia, Li C; Ai, Dongmei; Cram, Jacob A; Liang, Xiaoyi; Fuhrman, Jed A; Sun, Fengzhu

2015-09-21

Local trend (i.e. shape) analysis of time series data reveals co-changing patterns in dynamics of biological systems. However, slow permutation procedures to evaluate the statistical significance of local trend scores have limited its applications to high-throughput time series data analysis, e.g., data from the next generation sequencing technology based studies. By extending the theories for the tail probability of the range of sum of Markovian random variables, we propose formulae for approximating the statistical significance of local trend scores. Using simulations and real data, we show that the approximate p-value is close to that obtained using a large number of permutations (starting at time points >20 with no delay and >30 with delay of at most three time steps) in that the non-zero decimals of the p-values obtained by the approximation and the permutations are mostly the same when the approximate p-value is less than 0.05. In addition, the approximate p-value is slightly larger than that based on permutations making hypothesis testing based on the approximate p-value conservative. The approximation enables efficient calculation of p-values for pairwise local trend analysis, making large scale all-versus-all comparisons possible. We also propose a hybrid approach by integrating the approximation and permutations to obtain accurate p-values for significantly associated pairs. We further demonstrate its use with the analysis of the Polymouth Marine Laboratory (PML) microbial community time series from high-throughput sequencing data and found interesting organism co-occurrence dynamic patterns. The software tool is integrated into the eLSA software package that now provides accelerated local trend and similarity analysis pipelines for time series data. The package is freely available from the eLSA website: http://bitbucket.org/charade/elsa.

Test the Overall Significance of p-values by Using Joint Tail Probability of Ordered p-values as Test Statistic

OpenAIRE

Fang, Yongxiang; Wit, Ernst

2008-01-01

Fisher’s combined probability test is the most commonly used method to test the overall significance of a set independent p-values. However, it is very obviously that Fisher’s statistic is more sensitive to smaller p-values than to larger p-value and a small p-value may overrule the other p-values and decide the test result. This is, in some cases, viewed as a flaw. In order to overcome this flaw and improve the power of the test, the joint tail probability of a set p-values is proposed as a ...

Different modes of data processing and statistical testing applied to the same set of pharmaco-EEG recordings: effects on the evaluation of a selective and reversible MAO A inhibitor (brofaromine).

Science.gov (United States)

Reimann, I W; Jobert, M; Gleiter, C H; Turri, M; Bieck, P R; Herrmann, W M

1996-01-01

The comparison of two different modes of data processing and two different approaches to statistical testing both applied to the same set of EEG recordings was the main objective of this pharmacological study. Brofaromine (CGP 11,305 A), a new selective and reversible monoamine oxidase type A inhibitor was used as an example for investigating a potentially antidepressant drug in clinical development. The two modes of pharmaco-EEG (PEEG) data processing differed mainly in the sampling frequency and definition of spectral parameters. Patterns of significant changes were noted in terms of descriptive data analysis using either a nonparametric Wilcoxon signed-rank test or an ANOVA of transformed data, as suggested by Conover and Iman. These data clearly demonstrate that slight discrepancies in the results may simply arise from differences in data processing and statistical approach applied. In spite of these discrepancies, the pattern of brofaromine-induced PEEG changes was very similar regardless of the mode of data handling used.

After statistics reform : Should we still teach significance testing?

NARCIS (Netherlands)

A. Hak (Tony)

2014-01-01

textabstractIn the longer term null hypothesis significance testing (NHST) will disappear because p- values are not informative and not replicable. Should we continue to teach in the future the procedures of then abolished routines (i.e., NHST)? Three arguments are discussed for not teaching NHST in

Optimum Combination and Effect Analysis of Piezoresistor Dimensions in Micro Piezoresistive Pressure Sensor Using Design of Experiments and ANOVA: a Taguchi Approach

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Kirankumar B. Balavalad

2017-04-01

Full Text Available Piezoresistive (PZR pressure sensors have gained importance because of their robust construction, high sensitivity and good linearity. The conventional PZR pressure sensor consists of 4 piezoresistors placed on diaphragm and are connected in the form of Wheatstone bridge. These sensors convert stress applied on them into change in resistance, which is quantified into voltage using Wheatstone bridge mechanism. It is observed form the literature that, the dimensions of piezoresistors are very crucial in the performance of the piezoresistive pressure sensor. This paper presents, a novel mechanism of finding best combinations and effect of individual piezoresistors dimensions viz., Length, Width and Thickness, using DoE and ANOVA (Analysis of Variance method, following Taguchi experimentation approach. The paper presents a unique method to find optimum combination of piezoresistors dimensions and also clearly illustrates the effect the dimensions on the output of the sensor. The optimum combinations and the output response of sensor is predicted using DoE and the validation simulation is done. The result of the validation simulation is compared with the predicted value of sensor response i.e., V. Predicted value of V is 1.074 V and the validation simulation gave the response for V as 1.19 V. This actually validates that the model (DoE and ANOVA is adequate in describing V in terms of the variables defined.

Worry, Intolerance of Uncertainty, and Statistics Anxiety

Science.gov (United States)

Williams, Amanda S.

2013-01-01

Statistics anxiety is a problem for most graduate students. This study investigates the relationship between intolerance of uncertainty, worry, and statistics anxiety. Intolerance of uncertainty was significantly related to worry, and worry was significantly related to three types of statistics anxiety. Six types of statistics anxiety were…

Analysis of half diallel mating designs I: a practical analysis procedure for ANOVA approximation.

Science.gov (United States)

G.R. Johnson; J.N. King

1998-01-01

Procedures to analyze half-diallel mating designs using the SAS statistical package are presented. The procedure requires two runs of PROC and VARCOMP and results in estimates of additive and non-additive genetic variation. The procedures described can be modified to work on most statistical software packages which can compute variance component estimates. The...

Reducing statistics anxiety and enhancing statistics learning achievement: effectiveness of a one-minute strategy.

Science.gov (United States)

Chiou, Chei-Chang; Wang, Yu-Min; Lee, Li-Tze

2014-08-01

Statistical knowledge is widely used in academia; however, statistics teachers struggle with the issue of how to reduce students' statistics anxiety and enhance students' statistics learning. This study assesses the effectiveness of a "one-minute paper strategy" in reducing students' statistics-related anxiety and in improving students' statistics-related achievement. Participants were 77 undergraduates from two classes enrolled in applied statistics courses. An experiment was implemented according to a pretest/posttest comparison group design. The quasi-experimental design showed that the one-minute paper strategy significantly reduced students' statistics anxiety and improved students' statistics learning achievement. The strategy was a better instructional tool than the textbook exercise for reducing students' statistics anxiety and improving students' statistics achievement.

Evaluation of significantly modified water bodies in Vojvodina by using multivariate statistical techniques

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Vujović Svetlana R.

2013-01-01

Full Text Available This paper illustrates the utility of multivariate statistical techniques for analysis and interpretation of water quality data sets and identification of pollution sources/factors with a view to get better information about the water quality and design of monitoring network for effective management of water resources. Multivariate statistical techniques, such as factor analysis (FA/principal component analysis (PCA and cluster analysis (CA, were applied for the evaluation of variations and for the interpretation of a water quality data set of the natural water bodies obtained during 2010 year of monitoring of 13 parameters at 33 different sites. FA/PCA attempts to explain the correlations between the observations in terms of the underlying factors, which are not directly observable. Factor analysis is applied to physico-chemical parameters of natural water bodies with the aim classification and data summation as well as segmentation of heterogeneous data sets into smaller homogeneous subsets. Factor loadings were categorized as strong and moderate corresponding to the absolute loading values of >0.75, 0.75-0.50, respectively. Four principal factors were obtained with Eigenvalues >1 summing more than 78 % of the total variance in the water data sets, which is adequate to give good prior information regarding data structure. Each factor that is significantly related to specific variables represents a different dimension of water quality. The first factor F1 accounting for 28 % of the total variance and represents the hydrochemical dimension of water quality. The second factor F2 accounting for 18% of the total variance and may be taken factor of water eutrophication. The third factor F3 accounting 17 % of the total variance and represents the influence of point sources of pollution on water quality. The fourth factor F4 accounting 13 % of the total variance and may be taken as an ecological dimension of water quality. Cluster analysis (CA is an

Testing earthquake prediction algorithms: Statistically significant advance prediction of the largest earthquakes in the Circum-Pacific, 1992-1997

Science.gov (United States)

Kossobokov, V.G.; Romashkova, L.L.; Keilis-Borok, V. I.; Healy, J.H.

1999-01-01

Algorithms M8 and MSc (i.e., the Mendocino Scenario) were used in a real-time intermediate-term research prediction of the strongest earthquakes in the Circum-Pacific seismic belt. Predictions are made by M8 first. Then, the areas of alarm are reduced by MSc at the cost that some earthquakes are missed in the second approximation of prediction. In 1992-1997, five earthquakes of magnitude 8 and above occurred in the test area: all of them were predicted by M8 and MSc identified correctly the locations of four of them. The space-time volume of the alarms is 36% and 18%, correspondingly, when estimated with a normalized product measure of empirical distribution of epicenters and uniform time. The statistical significance of the achieved results is beyond 99% both for M8 and MSc. For magnitude 7.5 + , 10 out of 19 earthquakes were predicted by M8 in 40% and five were predicted by M8-MSc in 13% of the total volume considered. This implies a significance level of 81% for M8 and 92% for M8-MSc. The lower significance levels might result from a global change in seismic regime in 1993-1996, when the rate of the largest events has doubled and all of them become exclusively normal or reversed faults. The predictions are fully reproducible; the algorithms M8 and MSc in complete formal definitions were published before we started our experiment [Keilis-Borok, V.I., Kossobokov, V.G., 1990. Premonitory activation of seismic flow: Algorithm M8, Phys. Earth and Planet. Inter. 61, 73-83; Kossobokov, V.G., Keilis-Borok, V.I., Smith, S.W., 1990. Localization of intermediate-term earthquake prediction, J. Geophys. Res., 95, 19763-19772; Healy, J.H., Kossobokov, V.G., Dewey, J.W., 1992. A test to evaluate the earthquake prediction algorithm, M8. U.S. Geol. Surv. OFR 92-401]. M8 is available from the IASPEI Software Library [Healy, J.H., Keilis-Borok, V.I., Lee, W.H.K. (Eds.), 1997. Algorithms for Earthquake Statistics and Prediction, Vol. 6. IASPEI Software Library]. ?? 1999 Elsevier

Olive mill wastewater characteristics: modelling and statistical analysis

Directory of Open Access Journals (Sweden)

Martins-Dias, Susete

2004-09-01

Full Text Available A synthesis of the work carried out on Olive Mill Wastewater (OMW characterisation is given, covering articles published over the last 50 years. Data on OMW characterisation found in the literature are summarised and correlations between them and with phenolic compounds content are sought. This permits the characteristics of an OMW to be estimated from one simple measurement: the phenolic compounds concentration. A model based on OMW characterisations accounting 6 countries was developed along with a model for Portuguese OMW. The statistical analysis of the correlations obtained indicates that Chemical Oxygen Demand of a given OMW is a second-degree polynomial function of its phenolic compounds concentration. Tests to evaluate the regressions significance were carried out, based on multivariable ANOVA analysis, on visual standardised residuals distribution and their means for confidence levels of 95 and 99 %, validating clearly these models. This modelling work will help in the future planning, operation and monitoring of an OMW treatment plant.Presentamos una síntesis de los trabajos realizados en los últimos 50 años relacionados con la caracterización del alpechín. Realizamos una recopilación de los datos publicados, buscando correlaciones entre los datos relativos al alpechín y los compuestos fenólicos. Esto permite la determinación de las características del alpechín a partir de una sola medida: La concentración de compuestos fenólicos. Proponemos dos modelos, uno basado en datos relativos a seis países y un segundo aplicado únicamente a Portugal. El análisis estadístico de las correlaciones obtenidas indica que la demanda química de oxígeno de un determinado alpechín es una función polinómica de segundo grado de su concentración de compuestos fenólicos. Se comprobó la significancia de esta correlación mediante la aplicación del análisis multivariable ANOVA, y además se evaluó la distribución de residuos y sus

A novel complete-case analysis to determine statistical significance between treatments in an intention-to-treat population of randomized clinical trials involving missing data.

Science.gov (United States)

Liu, Wei; Ding, Jinhui

2018-04-01

The application of the principle of the intention-to-treat (ITT) to the analysis of clinical trials is challenged in the presence of missing outcome data. The consequences of stopping an assigned treatment in a withdrawn subject are unknown. It is difficult to make a single assumption about missing mechanisms for all clinical trials because there are complicated reactions in the human body to drugs due to the presence of complex biological networks, leading to data missing randomly or non-randomly. Currently there is no statistical method that can tell whether a difference between two treatments in the ITT population of a randomized clinical trial with missing data is significant at a pre-specified level. Making no assumptions about the missing mechanisms, we propose a generalized complete-case (GCC) analysis based on the data of completers. An evaluation of the impact of missing data on the ITT analysis reveals that a statistically significant GCC result implies a significant treatment effect in the ITT population at a pre-specified significance level unless, relative to the comparator, the test drug is poisonous to the non-completers as documented in their medical records. Applications of the GCC analysis are illustrated using literature data, and its properties and limits are discussed.

The analysis of morphometric data on rocky mountain wolves and artic wolves using statistical method

Science.gov (United States)

Ammar Shafi, Muhammad; Saifullah Rusiman, Mohd; Hamzah, Nor Shamsidah Amir; Nor, Maria Elena; Ahmad, Noor’ani; Azia Hazida Mohamad Azmi, Nur; Latip, Muhammad Faez Ab; Hilmi Azman, Ahmad

2018-04-01

Morphometrics is a quantitative analysis depending on the shape and size of several specimens. Morphometric quantitative analyses are commonly used to analyse fossil record, shape and size of specimens and others. The aim of the study is to find the differences between rocky mountain wolves and arctic wolves based on gender. The sample utilised secondary data which included seven variables as independent variables and two dependent variables. Statistical modelling was used in the analysis such was the analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA). The results showed there exist differentiating results between arctic wolves and rocky mountain wolves based on independent factors and gender.

Statistical evaluation of the mechanical properties of high-volume class F fly ash concretes

KAUST Repository

Yoon, Seyoon

2014-03-01

High-Volume Fly Ash (HVFA) concretes are seen by many as a feasible solution for sustainable, low embodied carbon construction. At the moment, fly ash is classified as a waste by-product, primarily of thermal power stations. In this paper the authors experimentally and statistically investigated the effects of mix-design factors on the mechanical properties of high-volume class F fly ash concretes. A total of 240 and 32 samples were produced and tested in the laboratory to measure compressive strength and Young\\'s modulus respectively. Applicability of the CEB-FIP (Comite Euro-international du Béton - Fédération Internationale de la Précontrainte) and ACI (American Concrete Institute) Building Model Code (Thomas, 2010; ACI Committee 209, 1982) [1,2] to the experimentally-derived mechanical property data for HVFA concretes was established. Furthermore, using multiple linear regression analysis, Mean Squared Residuals (MSRs) were obtained to determine whether a weight- or volume-based mix proportion is better to predict the mechanical properties of HVFA concrete. The significance levels of the design factors, which indicate how significantly the factors affect the HVFA concrete\\'s mechanical properties, were determined using analysis of variance (ANOVA) tests. The results show that a weight-based mix proportion is a slightly better predictor of mechanical properties than volume-based one. The significance level of fly ash substitution rate was higher than that of w/b ratio initially but reduced over time. © 2014 Elsevier Ltd. All rights reserved.

Violation of the Sphericity Assumption and Its Effect on Type-I Error Rates in Repeated Measures ANOVA and Multi-Level Linear Models (MLM).

Science.gov (United States)

Haverkamp, Nicolas; Beauducel, André

2017-01-01

We investigated the effects of violations of the sphericity assumption on Type I error rates for different methodical approaches of repeated measures analysis using a simulation approach. In contrast to previous simulation studies on this topic, up to nine measurement occasions were considered. Effects of the level of inter-correlations between measurement occasions on Type I error rates were considered for the first time. Two populations with non-violation of the sphericity assumption, one with uncorrelated measurement occasions and one with moderately correlated measurement occasions, were generated. One population with violation of the sphericity assumption combines uncorrelated with highly correlated measurement occasions. A second population with violation of the sphericity assumption combines moderately correlated and highly correlated measurement occasions. From these four populations without any between-group effect or within-subject effect 5,000 random samples were drawn. Finally, the mean Type I error rates for Multilevel linear models (MLM) with an unstructured covariance matrix (MLM-UN), MLM with compound-symmetry (MLM-CS) and for repeated measures analysis of variance (rANOVA) models (without correction, with Greenhouse-Geisser-correction, and Huynh-Feldt-correction) were computed. To examine the effect of both the sample size and the number of measurement occasions, sample sizes of n = 20, 40, 60, 80, and 100 were considered as well as measurement occasions of m = 3, 6, and 9. With respect to rANOVA, the results plead for a use of rANOVA with Huynh-Feldt-correction, especially when the sphericity assumption is violated, the sample size is rather small and the number of measurement occasions is large. For MLM-UN, the results illustrate a massive progressive bias for small sample sizes ( n = 20) and m = 6 or more measurement occasions. This effect could not be found in previous simulation studies with a smaller number of measurement occasions. The

Orthopantomographic evaluation of canine and first premolar using Demirjian's stages in central India: new approach to forensic age estimation.

Science.gov (United States)

Pathak, Hrishikesh V; Dixit, Pradeep; Shrigiriwar, Manish; Bardale, Rajesh

2012-07-01

Teeth development is widely used for age estimation in forensic science. The aims of this study were as follows: first, to establish Indian data on canine and first premolar development for age estimation and second, to investigate population differences in teeth development. Orthopantomograms of 340 Indian children aged between 5 and 14 years were analyzed. Demirjian's stages were recorded for the developmental evaluation of canine and first premolar and for further descriptive statistical analysis. A two-way ANOVA was performed to test the significance of difference in teeth development by sex and stage. A one-way ANOVA was performed to investigate population differences in teeth development. Results showed statistically significant differences in teeth development by sex and stage. Accordingly, teeth development was earlier in girls. No statistically significant differences were observed in timings of Demirjian's stages among different populations. In conclusion, the findings of this study could be used for age estimation of Indian children. © 2012 American Academy of Forensic Sciences.

Estimating linear effects in ANOVA designs: the easy way.

Science.gov (United States)

Pinhas, Michal; Tzelgov, Joseph; Ganor-Stern, Dana

2012-09-01

Research in cognitive science has documented numerous phenomena that are approximated by linear relationships. In the domain of numerical cognition, the use of linear regression for estimating linear effects (e.g., distance and SNARC effects) became common following Fias, Brysbaert, Geypens, and d'Ydewalle's (1996) study on the SNARC effect. While their work has become the model for analyzing linear effects in the field, it requires statistical analysis of individual participants and does not provide measures of the proportions of variability accounted for (cf. Lorch & Myers, 1990). In the present methodological note, using both the distance and SNARC effects as examples, we demonstrate how linear effects can be estimated in a simple way within the framework of repeated measures analysis of variance. This method allows for estimating effect sizes in terms of both slope and proportions of variability accounted for. Finally, we show that our method can easily be extended to estimate linear interaction effects, not just linear effects calculated as main effects.

A statistical model for investigating binding probabilities of DNA nucleotide sequences using microarrays.

Science.gov (United States)

Lee, Mei-Ling Ting; Bulyk, Martha L; Whitmore, G A; Church, George M

2002-12-01

There is considerable scientific interest in knowing the probability that a site-specific transcription factor will bind to a given DNA sequence. Microarray methods provide an effective means for assessing the binding affinities of a large number of DNA sequences as demonstrated by Bulyk et al. (2001, Proceedings of the National Academy of Sciences, USA 98, 7158-7163) in their study of the DNA-binding specificities of Zif268 zinc fingers using microarray technology. In a follow-up investigation, Bulyk, Johnson, and Church (2002, Nucleic Acid Research 30, 1255-1261) studied the interdependence of nucleotides on the binding affinities of transcription proteins. Our article is motivated by this pair of studies. We present a general statistical methodology for analyzing microarray intensity measurements reflecting DNA-protein interactions. The log probability of a protein binding to a DNA sequence on an array is modeled using a linear ANOVA model. This model is convenient because it employs familiar statistical concepts and procedures and also because it is effective for investigating the probability structure of the binding mechanism.

Evaluating statistical and clinical significance of intervention effects in single-case experimental designs: an SPSS method to analyze univariate data.

Science.gov (United States)

Maric, Marija; de Haan, Else; Hogendoorn, Sanne M; Wolters, Lidewij H; Huizenga, Hilde M

2015-03-01

Single-case experimental designs are useful methods in clinical research practice to investigate individual client progress. Their proliferation might have been hampered by methodological challenges such as the difficulty applying existing statistical procedures. In this article, we describe a data-analytic method to analyze univariate (i.e., one symptom) single-case data using the common package SPSS. This method can help the clinical researcher to investigate whether an intervention works as compared with a baseline period or another intervention type, and to determine whether symptom improvement is clinically significant. First, we describe the statistical method in a conceptual way and show how it can be implemented in SPSS. Simulation studies were performed to determine the number of observation points required per intervention phase. Second, to illustrate this method and its implications, we present a case study of an adolescent with anxiety disorders treated with cognitive-behavioral therapy techniques in an outpatient psychotherapy clinic, whose symptoms were regularly assessed before each session. We provide a description of the data analyses and results of this case study. Finally, we discuss the advantages and shortcomings of the proposed method. Copyright © 2014. Published by Elsevier Ltd.

Performance studies of GooFit on GPUs vs RooFit on CPUs while estimating the statistical significance of a new physical signal

Science.gov (United States)

Di Florio, Adriano

2017-10-01

In order to test the computing capabilities of GPUs with respect to traditional CPU cores a high-statistics toy Monte Carlo technique has been implemented both in ROOT/RooFit and GooFit frameworks with the purpose to estimate the statistical significance of the structure observed by CMS close to the kinematical boundary of the J/ψϕ invariant mass in the three-body decay B + → J/ψϕK +. GooFit is a data analysis open tool under development that interfaces ROOT/RooFit to CUDA platform on nVidia GPU. The optimized GooFit application running on GPUs hosted by servers in the Bari Tier2 provides striking speed-up performances with respect to the RooFit application parallelised on multiple CPUs by means of PROOF-Lite tool. The considerable resulting speed-up, evident when comparing concurrent GooFit processes allowed by CUDA Multi Process Service and a RooFit/PROOF-Lite process with multiple CPU workers, is presented and discussed in detail. By means of GooFit it has also been possible to explore the behaviour of a likelihood ratio test statistic in different situations in which the Wilks Theorem may or may not apply because its regularity conditions are not satisfied.

SOCR Analyses: Implementation and Demonstration of a New Graphical Statistics Educational Toolkit

Directory of Open Access Journals (Sweden)

Annie Chu

2009-04-01

Full Text Available The web-based, Java-written SOCR (Statistical Online Computational Resource toolshave been utilized in many undergraduate and graduate level statistics courses for sevenyears now (Dinov 2006; Dinov et al. 2008b. It has been proven that these resourcescan successfully improve students' learning (Dinov et al. 2008b. Being rst publishedonline in 2005, SOCR Analyses is a somewhat new component and it concentrate on datamodeling for both parametric and non-parametric data analyses with graphical modeldiagnostics. One of the main purposes of SOCR Analyses is to facilitate statistical learn-ing for high school and undergraduate students. As we have already implemented SOCRDistributions and Experiments, SOCR Analyses and Charts fulll the rest of a standardstatistics curricula. Currently, there are four core components of SOCR Analyses. Linearmodels included in SOCR Analyses are simple linear regression, multiple linear regression,one-way and two-way ANOVA. Tests for sample comparisons include t-test in the para-metric category. Some examples of SOCR Analyses' in the non-parametric category areWilcoxon rank sum test, Kruskal-Wallis test, Friedman's test, Kolmogorov-Smirno testand Fligner-Killeen test. Hypothesis testing models include contingency table, Friedman'stest and Fisher's exact test. The last component of Analyses is a utility for computingsample sizes for normal distribution. In this article, we present the design framework,computational implementation and the utilization of SOCR Analyses.

Foliar Sprays of Citric Acid and Malic Acid Modify Growth, Flowering, and Root to Shoot Ratio of Gazania (Gazania rigens L.: A Comparative Analysis by ANOVA and Structural Equations Modeling

Directory of Open Access Journals (Sweden)

Majid Talebi

2014-01-01

Full Text Available Foliar application of two levels of citric acid and malic acid (100 or 300 mg L−1 was investigated on flower stem height, plant height, flower performance and yield indices (fresh yield, dry yield and root to shoot ratio of Gazania. Distilled water was applied as control treatment. Multivariate analysis revealed that while the experimental treatments had no significant effect on fresh weight and the flower count, the plant dry weight was significantly increased by 300 mg L−1 malic acid. Citric acid at 100 and 300 mg L−1 and 300 mg L−1 malic acid increased the root fresh weight significantly. Both the plant height and peduncle length were significantly increased in all applied levels of citric acid and malic acid. The display time of flowers on the plant increased in all treatments compared to control treatment. The root to shoot ratio was increased significantly in 300 mg L−1 citric acid compared to all other treatments. These findings confirm earlier reports that citric acid and malic acid as environmentally sound chemicals are effective on various aspects of growth and development of crops. Structural equations modeling is used in parallel to ANOVA to conclude the factor effects and the possible path of effects.

Robust statistical methods for significance evaluation and applications in cancer driver detection and biomarker discovery

DEFF Research Database (Denmark)

Madsen, Tobias

2017-01-01

In the present thesis I develop, implement and apply statistical methods for detecting genomic elements implicated in cancer development and progression. This is done in two separate bodies of work. The first uses the somatic mutation burden to distinguish cancer driver mutations from passenger m...

Power of mental health nursing research: a statistical analysis of studies in the International Journal of Mental Health Nursing.

Science.gov (United States)

Gaskin, Cadeyrn J; Happell, Brenda

2013-02-01

Having sufficient power to detect effect sizes of an expected magnitude is a core consideration when designing studies in which inferential statistics will be used. The main aim of this study was to investigate the statistical power in studies published in the International Journal of Mental Health Nursing. From volumes 19 (2010) and 20 (2011) of the journal, studies were analysed for their power to detect small, medium, and large effect sizes, according to Cohen's guidelines. The power of the 23 studies included in this review to detect small, medium, and large effects was 0.34, 0.79, and 0.94, respectively. In 90% of papers, no adjustments for experiment-wise error were reported. With a median of nine inferential tests per paper, the mean experiment-wise error rate was 0.51. A priori power analyses were only reported in 17% of studies. Although effect sizes for correlations and regressions were routinely reported, effect sizes for other tests (χ(2)-tests, t-tests, ANOVA/MANOVA) were largely absent from the papers. All types of effect sizes were infrequently interpreted. Researchers are strongly encouraged to conduct power analyses when designing studies, and to avoid scattergun approaches to data analysis (i.e. undertaking large numbers of tests in the hope of finding 'significant' results). Because reviewing effect sizes is essential for determining the clinical significance of study findings, researchers would better serve the field of mental health nursing if they reported and interpreted effect sizes. © 2012 The Authors. International Journal of Mental Health Nursing © 2012 Australian College of Mental Health Nurses Inc.

Development and Statistical Validation of Spectrophotometric Methods for the Estimation of Nabumetone in Tablet Dosage Form

Directory of Open Access Journals (Sweden)

A. R. Rote

2010-01-01

Full Text Available Three new simple, economic spectrophotometric methods were developed and validated for the estimation of nabumetone in bulk and tablet dosage form. First method includes determination of nabumetone at absorption maxima 330 nm, second method applied was area under curve for analysis of nabumetone in the wavelength range of 326-334 nm and third method was First order derivative spectra with scaling factor 4. Beer law obeyed in the concentration range of 10-30 μg/mL for all three methods. The correlation coefficients were found to be 0.9997, 0.9998 and 0.9998 by absorption maxima, area under curve and first order derivative spectra. Results of analysis were validated statistically and by performing recovery studies. The mean percent recoveries were found satisfactory for all three methods. The developed methods were also compared statistically using one way ANOVA. The proposed methods have been successfully applied for the estimation of nabumetone in bulk and pharmaceutical tablet dosage form.

Gauging Skills of Hospital Security Personnel: a Statistically-driven, Questionnaire-based Approach.

Science.gov (United States)

Rinkoo, Arvind Vashishta; Mishra, Shubhra; Rahesuddin; Nabi, Tauqeer; Chandra, Vidha; Chandra, Hem

2013-01-01

This study aims to gauge the technical and soft skills of the hospital security personnel so as to enable prioritization of their training needs. A cross sectional questionnaire based study was conducted in December 2011. Two separate predesigned and pretested questionnaires were used for gauging soft skills and technical skills of the security personnel. Extensive statistical analysis, including Multivariate Analysis (Pillai-Bartlett trace along with Multi-factorial ANOVA) and Post-hoc Tests (Bonferroni Test) was applied. The 143 participants performed better on the soft skills front with an average score of 6.43 and standard deviation of 1.40. The average technical skills score was 5.09 with a standard deviation of 1.44. The study avowed a need for formal hands on training with greater emphasis on technical skills. Multivariate analysis of the available data further helped in identifying 20 security personnel who should be prioritized for soft skills training and a group of 36 security personnel who should receive maximum attention during technical skills training. This statistically driven approach can be used as a prototype by healthcare delivery institutions worldwide, after situation specific customizations, to identify the training needs of any category of healthcare staff.

Significance evaluation in factor graphs

DEFF Research Database (Denmark)

Madsen, Tobias; Hobolth, Asger; Jensen, Jens Ledet

2017-01-01

in genomics and the multiple-testing issues accompanying them, accurate significance evaluation is of great importance. We here address the problem of evaluating statistical significance of observations from factor graph models. Results Two novel numerical approximations for evaluation of statistical...... significance are presented. First a method using importance sampling. Second a saddlepoint approximation based method. We develop algorithms to efficiently compute the approximations and compare them to naive sampling and the normal approximation. The individual merits of the methods are analysed both from....... Conclusions The applicability of saddlepoint approximation and importance sampling is demonstrated on known models in the factor graph framework. Using the two methods we can substantially improve computational cost without compromising accuracy. This contribution allows analyses of large datasets...

DSC, FT-IR, NIR, NIR-PCA and NIR-ANOVA for determination of chemical stability of diuretic drugs: impact of excipients

Directory of Open Access Journals (Sweden)

Gumieniczek Anna

2018-03-01

Full Text Available It is well known that drugs can directly react with excipients. In addition, excipients can be a source of impurities that either directly react with drugs or catalyze their degradation. Thus, binary mixtures of three diuretics, torasemide, furosemide and amiloride with different excipients, i.e. citric acid anhydrous, povidone K25 (PVP, magnesium stearate (Mg stearate, lactose, D-mannitol, glycine, calcium hydrogen phosphate anhydrous (CaHPO4 and starch, were examined to detect interactions. High temperature and humidity or UV/VIS irradiation were applied as stressing conditions. Differential scanning calorimetry (DSC, FT-IR and NIR were used to adequately collect information. In addition, chemometric assessments of NIR signals with principal component analysis (PCA and ANOVA were applied.

Statistical approach of measurement of signal to noise ratio in according to change pulse sequence on brain MRI meningioma and cyst images

International Nuclear Information System (INIS)

Lee, Eul Kyu; Choi, Kwan Woo; Jeong, Hoi Woun; Jang, Seo Goo; Kim, Ki Won; Son, Soon Yong; Min, Jung Whan; Son, Jin Hyun

2016-01-01

The purpose of this study was to needed basis of measure MRI CAD development for signal to noise ratio (SNR) by pulse sequence analysis from region of interest (ROI) in brain magnetic resonance imaging (MRI) contrast. We examined images of brain MRI contrast enhancement of 117 patients, from January 2005 to December 2015 in a University-affiliated hospital, Seoul, Korea. Diagnosed as one of two brain diseases such as meningioma and cysts SNR for each patient's image of brain MRI were calculated by using Image J. Differences of SNR among two brain diseases were tested by SPSS Statistics21 ANOVA test for there was statistical significance (p < 0.05). We have analysis socio-demographical variables, SNR according to sequence disease, 95% confidence according to SNR of sequence and difference in a mean of SNR. Meningioma results, with the quality of distributions in the order of T1CE, T2 and T1, FLAIR. Cysts results, with the quality of distributions in the order of T2 and T1, T1CE and FLAIR. SNR of MRI sequences of the brain would be useful to classify disease. Therefore, this study will contribute to evaluate brain diseases, and be a fundamental to enhancing the accuracy of CAD development

Statistical approach of measurement of signal to noise ratio in according to change pulse sequence on brain MRI meningioma and cyst images

Energy Technology Data Exchange (ETDEWEB)

Lee, Eul Kyu [Inje Paik University Hospital Jeo-dong, Seoul (Korea, Republic of); Choi, Kwan Woo [Asan Medical Center, Seoul (Korea, Republic of); Jeong, Hoi Woun [The Baekseok Culture University, Cheonan (Korea, Republic of); Jang, Seo Goo [The Soonchunhyang University, Asan (Korea, Republic of); Kim, Ki Won [Kyung Hee University Hospital at Gang-dong, Seoul (Korea, Republic of); Son, Soon Yong [The Wonkwang Health Science University, Iksan (Korea, Republic of); Min, Jung Whan; Son, Jin Hyun [The Shingu University, Sungnam (Korea, Republic of)

2016-09-15

The purpose of this study was to needed basis of measure MRI CAD development for signal to noise ratio (SNR) by pulse sequence analysis from region of interest (ROI) in brain magnetic resonance imaging (MRI) contrast. We examined images of brain MRI contrast enhancement of 117 patients, from January 2005 to December 2015 in a University-affiliated hospital, Seoul, Korea. Diagnosed as one of two brain diseases such as meningioma and cysts SNR for each patient's image of brain MRI were calculated by using Image J. Differences of SNR among two brain diseases were tested by SPSS Statistics21 ANOVA test for there was statistical significance (p < 0.05). We have analysis socio-demographical variables, SNR according to sequence disease, 95% confidence according to SNR of sequence and difference in a mean of SNR. Meningioma results, with the quality of distributions in the order of T1CE, T2 and T1, FLAIR. Cysts results, with the quality of distributions in the order of T2 and T1, T1CE and FLAIR. SNR of MRI sequences of the brain would be useful to classify disease. Therefore, this study will contribute to evaluate brain diseases, and be a fundamental to enhancing the accuracy of CAD development.

Cognition of and Demand for Education and Teaching in Medical Statistics in China: A Systematic Review and Meta-Analysis

Science.gov (United States)

Li, Gaoming; Yi, Dali; Wu, Xiaojiao; Liu, Xiaoyu; Zhang, Yanqi; Liu, Ling; Yi, Dong

2015-01-01

Background Although a substantial number of studies focus on the teaching and application of medical statistics in China, few studies comprehensively evaluate the recognition of and demand for medical statistics. In addition, the results of these various studies differ and are insufficiently comprehensive and systematic. Objectives This investigation aimed to evaluate the general cognition of and demand for medical statistics by undergraduates, graduates, and medical staff in China. Methods We performed a comprehensive database search related to the cognition of and demand for medical statistics from January 2007 to July 2014 and conducted a meta-analysis of non-controlled studies with sub-group analysis for undergraduates, graduates, and medical staff. Results There are substantial differences with respect to the cognition of theory in medical statistics among undergraduates (73.5%), graduates (60.7%), and medical staff (39.6%). The demand for theory in medical statistics is high among graduates (94.6%), undergraduates (86.1%), and medical staff (88.3%). Regarding specific statistical methods, the cognition of basic statistical methods is higher than of advanced statistical methods. The demand for certain advanced statistical methods, including (but not limited to) multiple analysis of variance (ANOVA), multiple linear regression, and logistic regression, is higher than that for basic statistical methods. The use rates of the Statistical Package for the Social Sciences (SPSS) software and statistical analysis software (SAS) are only 55% and 15%, respectively. Conclusion The overall statistical competence of undergraduates, graduates, and medical staff is insufficient, and their ability to practically apply their statistical knowledge is limited, which constitutes an unsatisfactory state of affairs for medical statistics education. Because the demand for skills in this area is increasing, the need to reform medical statistics education in China has become urgent

Statistical testing of the full-range leadership theory in nursing.

Science.gov (United States)

Kanste, Outi; Kääriäinen, Maria; Kyngäs, Helvi

2009-12-01

The aim of this study is to test statistically the structure of the full-range leadership theory in nursing. The data were gathered by postal questionnaires from nurses and nurse leaders working in healthcare organizations in Finland. A follow-up study was performed 1 year later. The sample consisted of 601 nurses and nurse leaders, and the follow-up study had 78 respondents. Theory was tested through structural equation modelling, standard regression analysis and two-way anova. Rewarding transformational leadership seems to promote and passive laissez-faire leadership to reduce willingness to exert extra effort, perceptions of leader effectiveness and satisfaction with the leader. Active management-by-exception seems to reduce willingness to exert extra effort and perception of leader effectiveness. Rewarding transformational leadership remained as a strong explanatory factor of all outcome variables measured 1 year later. The data supported the main structure of the full-range leadership theory, lending support to the universal nature of the theory.

Evaluation of haematological and plasma biochemical effects of ...

African Journals Online (AJOL)

TAYO AJIBADE

2012-11-01

Nov 1, 2012 ... African Journal of Biotechnology Vol. 11(88), pp. ... biochemical values revealed significant increase in total protein, albumin and aspartate amino transferase. However ... functions and damages to cellular membrane normally leads to the .... way analysis of variance (ANOVA) for statistical significance was.

Statistical lamb wave localization based on extreme value theory

Science.gov (United States)

Harley, Joel B.

2018-04-01

Guided wave localization methods based on delay-and-sum imaging, matched field processing, and other techniques have been designed and researched to create images that locate and describe structural damage. The maximum value of these images typically represent an estimated damage location. Yet, it is often unclear if this maximum value, or any other value in the image, is a statistically significant indicator of damage. Furthermore, there are currently few, if any, approaches to assess the statistical significance of guided wave localization images. As a result, we present statistical delay-and-sum and statistical matched field processing localization methods to create statistically significant images of damage. Our framework uses constant rate of false alarm statistics and extreme value theory to detect damage with little prior information. We demonstrate our methods with in situ guided wave data from an aluminum plate to detect two 0.75 cm diameter holes. Our results show an expected improvement in statistical significance as the number of sensors increase. With seventeen sensors, both methods successfully detect damage with statistical significance.

An investigation on surface roughness of granite machined by ...

Indian Academy of Sciences (India)

Administrator

Additionally, the data obtained are evaluated statistically using the analysis of variance (ANOVA) to determine significant ..... The regression model is also an evidence of this powerful .... and appreciation for the financial support to TÜBİTAK.

The significance of Good Chair as part of children’s school and home environment in the preventive treatment of body statistics distortions

OpenAIRE

Mirosław Mrozkowiak; Hanna Żukowska

2015-01-01

Mrozkowiak Mirosław, Żukowska Hanna. Znaczenie Dobrego Krzesła, jako elementu szkolnego i domowego środowiska ucznia, w profilaktyce zaburzeń statyki postawy ciała = The significance of Good Chair as part of children’s school and home environment in the preventive treatment of body statistics distortions. Journal of Education, Health and Sport. 2015;5(7):179-215. ISSN 2391-8306. DOI 10.5281/zenodo.19832 http://ojs.ukw.edu.pl/index.php/johs/article/view/2015%3B5%287%29%3A179-215 https:...

Can a significance test be genuinely Bayesian?

OpenAIRE

Pereira, Carlos A. de B.; Stern, Julio Michael; Wechsler, Sergio

2008-01-01

The Full Bayesian Significance Test, FBST, is extensively reviewed. Its test statistic, a genuine Bayesian measure of evidence, is discussed in detail. Its behavior in some problems of statistical inference like testing for independence in contingency tables is discussed.

Statistical Approaches Used to Assess the Equity of Access to Food Outlets: A Systematic Review.

Science.gov (United States)

Lamb, Karen E; Thornton, Lukar E; Cerin, Ester; Ball, Kylie

2015-01-01

Inequalities in eating behaviours are often linked to the types of food retailers accessible in neighbourhood environments. Numerous studies have aimed to identify if access to healthy and unhealthy food retailers is socioeconomically patterned across neighbourhoods, and thus a potential risk factor for dietary inequalities. Existing reviews have examined differences between methodologies, particularly focussing on neighbourhood and food outlet access measure definitions. However, no review has informatively discussed the suitability of the statistical methodologies employed; a key issue determining the validity of study findings. Our aim was to examine the suitability of statistical approaches adopted in these analyses. Searches were conducted for articles published from 2000-2014. Eligible studies included objective measures of the neighbourhood food environment and neighbourhood-level socio-economic status, with a statistical analysis of the association between food outlet access and socio-economic status. Fifty-four papers were included. Outlet accessibility was typically defined as the distance to the nearest outlet from the neighbourhood centroid, or as the number of food outlets within a neighbourhood (or buffer). To assess if these measures were linked to neighbourhood disadvantage, common statistical methods included ANOVA, correlation, and Poisson or negative binomial regression. Although all studies involved spatial data, few considered spatial analysis techniques or spatial autocorrelation. With advances in GIS software, sophisticated measures of neighbourhood outlet accessibility can be considered. However, approaches to statistical analysis often appear less sophisticated. Care should be taken to consider assumptions underlying the analysis and the possibility of spatially correlated residuals which could affect the results.

Statistical Approaches Used to Assess the Equity of Access to Food Outlets: A Systematic Review

Directory of Open Access Journals (Sweden)

Karen E. Lamb

2015-07-01

Full Text Available BackgroundInequalities in eating behaviours are often linked to the types of food retailers accessible in neighbourhood environments. Numerous studies have aimed to identify if access to healthy and unhealthy food retailers is socioeconomically patterned across neighbourhoods, and thus a potential risk factor for dietary inequalities. Existing reviews have examined differences between methodologies, particularly focussing on neighbourhood and food outlet access measure definitions. However, no review has informatively discussed the suitability of the statistical methodologies employed; a key issue determining the validity of study findings. Our aim was to examine the suitability of statistical approaches adopted in these analyses.MethodsSearches were conducted for articles published from 2000-2014. Eligible studies included objective measures of the neighbourhood food environment and neighbourhood-level socio-economic status, with a statistical analysis of the association between food outlet access and socio-economic status.ResultsFifty-four papers were included. Outlet accessibility was typically defined as the distance to the nearest outlet from the neighbourhood centroid, or as the number of food outlets within a neighbourhood (or buffer. To assess if these measures were linked to neighbourhood disadvantage, common statistical methods included ANOVA, correlation, and Poisson or negative binomial regression. Although all studies involved spatial data, few considered spatial analysis techniques or spatial autocorrelation.ConclusionsWith advances in GIS software, sophisticated measures of neighbourhood outlet accessibility can be considered. However, approaches to statistical analysis often appear less sophisticated. Care should be taken to consider assumptions underlying the analysis and the possibility of spatially correlated residuals which could affect the results.

Statistics for experimentalists

CERN Document Server

Cooper, B E

2014-01-01

Statistics for Experimentalists aims to provide experimental scientists with a working knowledge of statistical methods and search approaches to the analysis of data. The book first elaborates on probability and continuous probability distributions. Discussions focus on properties of continuous random variables and normal variables, independence of two random variables, central moments of a continuous distribution, prediction from a normal distribution, binomial probabilities, and multiplication of probabilities and independence. The text then examines estimation and tests of significance. Topics include estimators and estimates, expected values, minimum variance linear unbiased estimators, sufficient estimators, methods of maximum likelihood and least squares, and the test of significance method. The manuscript ponders on distribution-free tests, Poisson process and counting problems, correlation and function fitting, balanced incomplete randomized block designs and the analysis of covariance, and experiment...

Com aplicar les proves paramètriques bivariades t de Student i ANOVA en SPSS. Cas pràctic

Directory of Open Access Journals (Sweden)

María-José Rubio-Hurtado

2012-07-01

Full Text Available Les proves paramètriques són un tipus de proves de significació estadística que quantifiquen l'associació o independència entre una variable quantitativa i una categòrica. Les proves paramètriques són exigents amb certs requisits previs per a la seva aplicació: la distribució Normal de la variable quantitativa en els grups que es comparen, l'homogeneïtat de variàncies en les poblacions de les quals procedeixen els grups i una n mostral no inferior a 30. El seu no compliment comporta la necessitat de recórrer a proves estadístiques no paramètriques. Les proves paramètriques es classifiquen en dos: prova t (per a una mostra o per a dues mostres relacionades o independents i prova ANOVA (per a més de dues mostres independents.

On two methods of statistical image analysis

NARCIS (Netherlands)

Missimer, J; Knorr, U; Maguire, RP; Herzog, H; Seitz, RJ; Tellman, L; Leenders, K.L.

1999-01-01

The computerized brain atlas (CBA) and statistical parametric mapping (SPM) are two procedures for voxel-based statistical evaluation of PET activation studies. Each includes spatial standardization of image volumes, computation of a statistic, and evaluation of its significance. In addition,

Statistics Using Just One Formula

Science.gov (United States)

Rosenthal, Jeffrey S.

2018-01-01

This article advocates that introductory statistics be taught by basing all calculations on a single simple margin-of-error formula and deriving all of the standard introductory statistical concepts (confidence intervals, significance tests, comparisons of means and proportions, etc) from that one formula. It is argued that this approach will…

Statistics Anxiety among Postgraduate Students

Science.gov (United States)

Koh, Denise; Zawi, Mohd Khairi

2014-01-01

Most postgraduate programmes, that have research components, require students to take at least one course of research statistics. Not all postgraduate programmes are science based, there are a significant number of postgraduate students who are from the social sciences that will be taking statistics courses, as they try to complete their…

K--12 science educator perception of instructing students with learning disabilities in the regular classroom

Science.gov (United States)

Holliday-Cashwell, Janet Rose

2000-10-01

variance. To test null hypothesis 2, ANOVA calculations were performed for each category identified in the demographics section of the data collection instrument under experience, current class level, and educational level. A total of six ANOVA calculations were performed. Three of the six ANOVA's revealed a statistical significance. Null hypothesis 2 was accepted because only three of the six ANOVA's revealed statistically significant differences: (a) two regarding mainstreaming and (b) one regarding inclusion.

Statistical experimental design for saltstone mixtures

International Nuclear Information System (INIS)

Harris, S.P.; Postles, R.L.

1992-01-01

The authors used a mixture experimental design for determining a window of operability for a process at the U.S. Department of Energy, Savannah River Site, Defense Waste Processing Facility (DWPF). The high-level radioactive waste at the Savannah River Site is stored in large underground carbon steel tanks. The waste consists of a supernate layer and a sludge layer. Cesium-137 will be removed from the supernate by precipitation and filtration. After further processing, the supernate layer will be fixed as a grout for disposal in concrete vaults. The remaining precipitate will be processed at the DWPF with treated waste tank sludge and glass-making chemicals into borosilicate glass. The leach-rate properties of the supernate grout formed from various mixes of solidified coefficients for NO 3 and chromium were used as a measure of leach rate. Various mixes of cement, Ca(OH) 2 , salt, slag, and fly ash were used. These constituents comprise the whole mix. Thus, a mixture experimental design was used. The regression procedure (PROC REG) in SAS was used to produce analysis of variance (ANOVA) statistics. In addition, detailed model diagnostics are readily available for identifying suspicious observations. For convenience, trillinear contour (TLC) plots, a standard graphics tool for examining mixture response surfaces, of the fitted model were produced using ECHIP

Statistical Reporting Errors and Collaboration on Statistical Analyses in Psychological Science.

Science.gov (United States)

Veldkamp, Coosje L S; Nuijten, Michèle B; Dominguez-Alvarez, Linda; van Assen, Marcel A L M; Wicherts, Jelte M

2014-01-01

Statistical analysis is error prone. A best practice for researchers using statistics would therefore be to share data among co-authors, allowing double-checking of executed tasks just as co-pilots do in aviation. To document the extent to which this 'co-piloting' currently occurs in psychology, we surveyed the authors of 697 articles published in six top psychology journals and asked them whether they had collaborated on four aspects of analyzing data and reporting results, and whether the described data had been shared between the authors. We acquired responses for 49.6% of the articles and found that co-piloting on statistical analysis and reporting results is quite uncommon among psychologists, while data sharing among co-authors seems reasonably but not completely standard. We then used an automated procedure to study the prevalence of statistical reporting errors in the articles in our sample and examined the relationship between reporting errors and co-piloting. Overall, 63% of the articles contained at least one p-value that was inconsistent with the reported test statistic and the accompanying degrees of freedom, and 20% of the articles contained at least one p-value that was inconsistent to such a degree that it may have affected decisions about statistical significance. Overall, the probability that a given p-value was inconsistent was over 10%. Co-piloting was not found to be associated with reporting errors.

Motivational Strategies and Possible Influence on Secondary School ...

African Journals Online (AJOL)

... and administered to the 360 teachers. The data collected were subjected to statistical analyses using ANOVA. The test yielded significant influence of motivational strategies on teachers' work performance. Based on the findings, recommendations were made. KEY WORDS: Motivational Strategies, Teaching Performance.

Confidence Intervals: From tests of statistical significance to confidence intervals, range hypotheses and substantial effects

Directory of Open Access Journals (Sweden)

Dominic Beaulieu-Prévost

2006-03-01

Full Text Available For the last 50 years of research in quantitative social sciences, the empirical evaluation of scientific hypotheses has been based on the rejection or not of the null hypothesis. However, more than 300 articles demonstrated that this method was problematic. In summary, null hypothesis testing (NHT is unfalsifiable, its results depend directly on sample size and the null hypothesis is both improbable and not plausible. Consequently, alternatives to NHT such as confidence intervals (CI and measures of effect size are starting to be used in scientific publications. The purpose of this article is, first, to provide the conceptual tools necessary to implement an approach based on confidence intervals, and second, to briefly demonstrate why such an approach is an interesting alternative to an approach based on NHT. As demonstrated in the article, the proposed CI approach avoids most problems related to a NHT approach and can often improve the scientific and contextual relevance of the statistical interpretations by testing range hypotheses instead of a point hypothesis and by defining the minimal value of a substantial effect. The main advantage of such a CI approach is that it replaces the notion of statistical power by an easily interpretable three-value logic (probable presence of a substantial effect, probable absence of a substantial effect and probabilistic undetermination. The demonstration includes a complete example.

Statistics 101 for Radiologists.

Science.gov (United States)

Anvari, Arash; Halpern, Elkan F; Samir, Anthony E

2015-10-01

Diagnostic tests have wide clinical applications, including screening, diagnosis, measuring treatment effect, and determining prognosis. Interpreting diagnostic test results requires an understanding of key statistical concepts used to evaluate test efficacy. This review explains descriptive statistics and discusses probability, including mutually exclusive and independent events and conditional probability. In the inferential statistics section, a statistical perspective on study design is provided, together with an explanation of how to select appropriate statistical tests. Key concepts in recruiting study samples are discussed, including representativeness and random sampling. Variable types are defined, including predictor, outcome, and covariate variables, and the relationship of these variables to one another. In the hypothesis testing section, we explain how to determine if observed differences between groups are likely to be due to chance. We explain type I and II errors, statistical significance, and study power, followed by an explanation of effect sizes and how confidence intervals can be used to generalize observed effect sizes to the larger population. Statistical tests are explained in four categories: t tests and analysis of variance, proportion analysis tests, nonparametric tests, and regression techniques. We discuss sensitivity, specificity, accuracy, receiver operating characteristic analysis, and likelihood ratios. Measures of reliability and agreement, including κ statistics, intraclass correlation coefficients, and Bland-Altman graphs and analysis, are introduced. © RSNA, 2015.

Preventing statistical errors in scientific journals.

NARCIS (Netherlands)

Nuijten, M.B.

2016-01-01

There is evidence for a high prevalence of statistical reporting errors in psychology and other scientific fields. These errors display a systematic preference for statistically significant results, distorting the scientific literature. There are several possible causes for this systematic error

Basics of statistical physics

CERN Document Server

Müller-Kirsten, Harald J W

2013-01-01

Statistics links microscopic and macroscopic phenomena, and requires for this reason a large number of microscopic elements like atoms. The results are values of maximum probability or of averaging. This introduction to statistical physics concentrates on the basic principles, and attempts to explain these in simple terms supplemented by numerous examples. These basic principles include the difference between classical and quantum statistics, a priori probabilities as related to degeneracies, the vital aspect of indistinguishability as compared with distinguishability in classical physics, the differences between conserved and non-conserved elements, the different ways of counting arrangements in the three statistics (Maxwell-Boltzmann, Fermi-Dirac, Bose-Einstein), the difference between maximization of the number of arrangements of elements, and averaging in the Darwin-Fowler method. Significant applications to solids, radiation and electrons in metals are treated in separate chapters, as well as Bose-Eins...

Renyi statistics in equilibrium statistical mechanics

International Nuclear Information System (INIS)

Parvan, A.S.; Biro, T.S.

2010-01-01

The Renyi statistics in the canonical and microcanonical ensembles is examined both in general and in particular for the ideal gas. In the microcanonical ensemble the Renyi statistics is equivalent to the Boltzmann-Gibbs statistics. By the exact analytical results for the ideal gas, it is shown that in the canonical ensemble, taking the thermodynamic limit, the Renyi statistics is also equivalent to the Boltzmann-Gibbs statistics. Furthermore it satisfies the requirements of the equilibrium thermodynamics, i.e. the thermodynamical potential of the statistical ensemble is a homogeneous function of first degree of its extensive variables of state. We conclude that the Renyi statistics arrives at the same thermodynamical relations, as those stemming from the Boltzmann-Gibbs statistics in this limit.

Teaching renewable energy using online PBL in investigating its effect on behaviour towards energy conservation among Malaysian students: ANOVA repeated measures approach

Science.gov (United States)

Nordin, Norfarah; Samsudin, Mohd Ali; Hadi Harun, Abdul

2017-01-01

This research aimed to investigate whether online problem based learning (PBL) approach to teach renewable energy topic improves students’ behaviour towards energy conservation. A renewable energy online problem based learning (REePBaL) instruction package was developed based on the theory of constructivism and adaptation of the online learning model. This study employed a single group quasi-experimental design to ascertain the changed in students’ behaviour towards energy conservation after underwent the intervention. The study involved 48 secondary school students in a Malaysian public school. ANOVA Repeated Measure technique was employed in order to compare scores of students’ behaviour towards energy conservation before and after the intervention. Based on the finding, students’ behaviour towards energy conservation improved after the intervention.

Preservice Teachers' Memories of Their Secondary Science Education Experiences

Science.gov (United States)

Hudson, Peter; Usak, Muhammet; Fancovicova, Jana; Erdogan, Mehmet; Prokop, Pavol

2010-01-01

Understanding preservice teachers' memories of their education may aid towards articulating high-impact teaching practices. This study describes 246 preservice teachers' perceptions of their secondary science education experiences through a questionnaire and 28-item survey. ANOVA was statistically significant about participants' memories of…

Water quality effects of harbour activities assessed with integrated ...

African Journals Online (AJOL)

Ecological tools were developed to study the water quality in Cochin harbour, a complex aquatic ecosystems, through the integration of microbiological monitoring (faecal coliforms and Pseudomonas species) and heavy metal contamination (lead, cadmium and mercury). One way ANOVA indicates statistically significant ...

Statistics: a Bayesian perspective

National Research Council Canada - National Science Library

Berry, Donald A

1996-01-01

...: it is the only introductory textbook based on Bayesian ideas, it combines concepts and methods, it presents statistics as a means of integrating data into the significant process, it develops ideas...

Predictive capacity of a non-radioisotopic local lymph node assay using flow cytometry, LLNA:BrdU-FCM: Comparison of a cutoff approach and inferential statistics.

Science.gov (United States)

Kim, Da-Eun; Yang, Hyeri; Jang, Won-Hee; Jung, Kyoung-Mi; Park, Miyoung; Choi, Jin Kyu; Jung, Mi-Sook; Jeon, Eun-Young; Heo, Yong; Yeo, Kyung-Wook; Jo, Ji-Hoon; Park, Jung Eun; Sohn, Soo Jung; Kim, Tae Sung; Ahn, Il Young; Jeong, Tae-Cheon; Lim, Kyung-Min; Bae, SeungJin

2016-01-01

In order for a novel test method to be applied for regulatory purposes, its reliability and relevance, i.e., reproducibility and predictive capacity, must be demonstrated. Here, we examine the predictive capacity of a novel non-radioisotopic local lymph node assay, LLNA:BrdU-FCM (5-bromo-2'-deoxyuridine-flow cytometry), with a cutoff approach and inferential statistics as a prediction model. 22 reference substances in OECD TG429 were tested with a concurrent positive control, hexylcinnamaldehyde 25%(PC), and the stimulation index (SI) representing the fold increase in lymph node cells over the vehicle control was obtained. The optimal cutoff SI (2.7≤cutoff <3.5), with respect to predictive capacity, was obtained by a receiver operating characteristic curve, which produced 90.9% accuracy for the 22 substances. To address the inter-test variability in responsiveness, SI values standardized with PC were employed to obtain the optimal percentage cutoff (42.6≤cutoff <57.3% of PC), which produced 86.4% accuracy. A test substance may be diagnosed as a sensitizer if a statistically significant increase in SI is elicited. The parametric one-sided t-test and non-parametric Wilcoxon rank-sum test produced 77.3% accuracy. Similarly, a test substance could be defined as a sensitizer if the SI means of the vehicle control, and of the low, middle, and high concentrations were statistically significantly different, which was tested using ANOVA or Kruskal-Wallis, with post hoc analysis, Dunnett, or DSCF (Dwass-Steel-Critchlow-Fligner), respectively, depending on the equal variance test, producing 81.8% accuracy. The absolute SI-based cutoff approach produced the best predictive capacity, however the discordant decisions between prediction models need to be examined further. Copyright © 2015 Elsevier Inc. All rights reserved.

Using the multiple regression analysis with respect to ANOVA and 3D mapping to model the actual performance of PEM (proton exchange membrane) fuel cell at various operating conditions

International Nuclear Information System (INIS)

Al-Hadeethi, Farqad; Al-Nimr, Moh'd; Al-Safadi, Mohammad

2015-01-01

The performance of PEM (proton exchange membrane) fuel cell was experimentally investigated at three temperatures (30, 50 and 70 °C), four flow rates (5, 10, 15 and 20 ml/min) and two flow patterns (co-current and counter current) in order to generate two correlations using multiple regression analysis with respect to ANOVA. Results revealed that increasing the temperature for co-current and counter current flow patterns will increase both hydrogen and oxygen diffusivities, water management and membrane conductivity. The derived mathematical correlations and three dimensional mapping (i.e. surface response) for the co-current and countercurrent flow patterns showed that there is a clear interaction among the various variables (temperatures and flow rates). - Highlights: • Generating mathematical correlations using multiple regression analysis with respect to ANOVA for the performance of the PEM fuel cell. • Using the 3D mapping to diagnose the optimum performance of the PEM fuel cell at the given operating conditions. • Results revealed that increasing the flow rate had direct influence on the consumption of oxygen. • Results assured that increasing the temperature in co-current and counter current flow patterns increases the performance of PEM fuel cell.

Statistical Analysis and Evaluation of the Depth of the Ruts on Lithuanian State Significance Roads

Directory of Open Access Journals (Sweden)

Erinijus Getautis

2011-04-01

Full Text Available The aim of this work is to gather information about the national flexible pavement roads ruts depth, to determine its statistical dispersijon index and to determine their validity for needed requirements. Analysis of scientific works of ruts apearance in the asphalt and their influence for driving is presented in this work. Dynamical models of ruts in asphalt are presented in the work as well. Experimental outcome data of rut depth dispersijon in the national highway of Lithuania Vilnius – Kaunas is prepared. Conclusions are formulated and presented. Article in Lithuanian

Perceived Statistical Knowledge Level and Self-Reported Statistical Practice Among Academic Psychologists

Directory of Open Access Journals (Sweden)

Laura Badenes-Ribera

2018-06-01

Full Text Available Introduction: Publications arguing against the null hypothesis significance testing (NHST procedure and in favor of good statistical practices have increased. The most frequently mentioned alternatives to NHST are effect size statistics (ES, confidence intervals (CIs, and meta-analyses. A recent survey conducted in Spain found that academic psychologists have poor knowledge about effect size statistics, confidence intervals, and graphic displays for meta-analyses, which might lead to a misinterpretation of the results. In addition, it also found that, although the use of ES is becoming generalized, the same thing is not true for CIs. Finally, academics with greater knowledge about ES statistics presented a profile closer to good statistical practice and research design. Our main purpose was to analyze the extension of these results to a different geographical area through a replication study.Methods: For this purpose, we elaborated an on-line survey that included the same items as the original research, and we asked academic psychologists to indicate their level of knowledge about ES, their CIs, and meta-analyses, and how they use them. The sample consisted of 159 Italian academic psychologists (54.09% women, mean age of 47.65 years. The mean number of years in the position of professor was 12.90 (SD = 10.21.Results: As in the original research, the results showed that, although the use of effect size estimates is becoming generalized, an under-reporting of CIs for ES persists. The most frequent ES statistics mentioned were Cohen's d and R2/η2, which can have outliers or show non-normality or violate statistical assumptions. In addition, academics showed poor knowledge about meta-analytic displays (e.g., forest plot and funnel plot and quality checklists for studies. Finally, academics with higher-level knowledge about ES statistics seem to have a profile closer to good statistical practices.Conclusions: Changing statistical practice is not

RBioplot: an easy-to-use R pipeline for automated statistical analysis and data visualization in molecular biology and biochemistry

Directory of Open Access Journals (Sweden)

Jing Zhang

2016-09-01

Full Text Available Background Statistical analysis and data visualization are two crucial aspects in molecular biology and biology. For analyses that compare one dependent variable between standard (e.g., control and one or multiple independent variables, a comprehensive yet highly streamlined solution is valuable. The computer programming language R is a popular platform for researchers to develop tools that are tailored specifically for their research needs. Here we present an R package RBioplot that takes raw input data for automated statistical analysis and plotting, highly compatible with various molecular biology and biochemistry lab techniques, such as, but not limited to, western blotting, PCR, and enzyme activity assays. Method The package is built based on workflows operating on a simple raw data layout, with minimum user input or data manipulation required. The package is distributed through GitHub, which can be easily installed through one single-line R command. A detailed installation guide is available at http://kenstoreylab.com/?page_id=2448. Users can also download demo datasets from the same website. Results and Discussion By integrating selected functions from existing statistical and data visualization packages with extensive customization, RBioplot features both statistical analysis and data visualization functionalities. Key properties of RBioplot include: -Fully automated and comprehensive statistical analysis, including normality test, equal variance test, Student’s t-test and ANOVA (with post-hoc tests; -Fully automated histogram, heatmap and joint-point curve plotting modules; -Detailed output files for statistical analysis, data manipulation and high quality graphs; -Axis range finding and user customizable tick settings; -High user-customizability.

Understanding Statistics - Cancer Statistics

Science.gov (United States)

Annual reports of U.S. cancer statistics including new cases, deaths, trends, survival, prevalence, lifetime risk, and progress toward Healthy People targets, plus statistical summaries for a number of common cancer types.

Funding source and primary outcome changes in clinical trials registered on ClinicalTrials.gov are associated with the reporting of a statistically significant primary outcome: a cross-sectional study [v2; ref status: indexed, http://f1000r.es/5bj

Directory of Open Access Journals (Sweden)

Sreeram V Ramagopalan

2015-04-01

Full Text Available Background: We and others have shown a significant proportion of interventional trials registered on ClinicalTrials.gov have their primary outcomes altered after the listed study start and completion dates. The objectives of this study were to investigate whether changes made to primary outcomes are associated with the likelihood of reporting a statistically significant primary outcome on ClinicalTrials.gov. Methods: A cross-sectional analysis of all interventional clinical trials registered on ClinicalTrials.gov as of 20 November 2014 was performed. The main outcome was any change made to the initially listed primary outcome and the time of the change in relation to the trial start and end date. Findings: 13,238 completed interventional trials were registered with ClinicalTrials.gov that also had study results posted on the website. 2555 (19.3% had one or more statistically significant primary outcomes. Statistical analysis showed that registration year, funding source and primary outcome change after trial completion were associated with reporting a statistically significant primary outcome. Conclusions: Funding source and primary outcome change after trial completion are associated with a statistically significant primary outcome report on clinicaltrials.gov.

Statistical analysis and data management

International Nuclear Information System (INIS)

Anon.

1981-01-01

This report provides an overview of the history of the WIPP Biology Program. The recommendations of the American Institute of Biological Sciences (AIBS) for the WIPP biology program are summarized. The data sets available for statistical analyses and problems associated with these data sets are also summarized. Biological studies base maps are presented. A statistical model is presented to evaluate any correlation between climatological data and small mammal captures. No statistically significant relationship between variance in small mammal captures on Dr. Gennaro's 90m x 90m grid and precipitation records from the Duval Potash Mine were found

Aplication of the statistical experimental design to optimize mine-impacted water (MIW) remediation using shrimp-shell.

Science.gov (United States)

Núñez-Gómez, Dámaris; Alves, Alcione Aparecida de Almeida; Lapolli, Flavio Rubens; Lobo-Recio, María A

2017-01-01

Mine-impacted water (MIW) is one of the most serious mining problems and has a high negative impact on water resources and aquatic life. The main characteristics of MIW are a low pH (between 2 and 4) and high concentrations of SO 4 2- and metal ions (Cd, Cu, Ni, Pb, Zn, Fe, Al, Cr, Mn, Mg, etc.), many of which are toxic to ecosystems and human life. Shrimp shell was selected as a MIW treatment agent because it is a low-cost metal-sorbent biopolymer with a high chitin content and contains calcium carbonate, an acid-neutralizing agent. To determine the best metal-removal conditions, a statistical study using statistical planning was carried out. Thus, the objective of this work was to identify the degree of influence and dependence of the shrimp-shell content for the removal of Fe, Al, Mn, Co, and Ni from MIW. In this study, a central composite rotational experimental design (CCRD) with a quadruplicate at the midpoint (2 2 ) was used to evaluate the joint influence of two formulation variables-agitation and the shrimp-shell content. The statistical results showed the significant influence (p < 0.05) of the agitation variable for Fe and Ni removal (linear and quadratic form, respectively) and of the shrimp-shell content variable for Mn (linear form), Al and Co (linear and quadratic form) removal. Analysis of variance (ANOVA) for Al, Co, and Ni removal showed that the model is valid at the 95% confidence interval and that no adjustment needed within the ranges evaluated of agitation (0-251.5 rpm) and shrimp-shell content (1.2-12.8 g L -1 ). The model required adjustments to the 90% and 75% confidence interval for Fe and Mn removal, respectively. In terms of efficiency in removing pollutants, it was possible to determine the best experimental values of the variables considered as 188 rpm and 9.36 g L -1 of shrimp-shells. Copyright © 2016 Elsevier Ltd. All rights reserved.

Confounding and Statistical Significance of Indirect Effects: Childhood Adversity, Education, Smoking, and Anxious and Depressive Symptomatology

Directory of Open Access Journals (Sweden)

Mashhood Ahmed Sheikh

2017-08-01

mediate the association between childhood adversity and ADS in adulthood. However, when education was excluded as a mediator-response confounding variable, the indirect effect of childhood adversity on ADS in adulthood was statistically significant (p < 0.05. This study shows that a careful inclusion of potential confounding variables is important when assessing mediation.

Survey of waste disposal methods in Awka metropolis | Bill | Journal ...

African Journals Online (AJOL)

Waste disposal methods commonly practiced in Awka metropolis, Anambra state were investigated from August to October, 2013. Data was analyzed with both descriptive statistics of frequency and percentages, and alternate hypotheses were tested using Analysis of Variance (ANOVA) at a significance level of 0.05.

[Big data in official statistics].

Science.gov (United States)

Zwick, Markus

2015-08-01

The concept of "big data" stands to change the face of official statistics over the coming years, having an impact on almost all aspects of data production. The tasks of future statisticians will not necessarily be to produce new data, but rather to identify and make use of existing data to adequately describe social and economic phenomena. Until big data can be used correctly in official statistics, a lot of questions need to be answered and problems solved: the quality of data, data protection, privacy, and the sustainable availability are some of the more pressing issues to be addressed. The essential skills of official statisticians will undoubtedly change, and this implies a number of challenges to be faced by statistical education systems, in universities, and inside the statistical offices. The national statistical offices of the European Union have concluded a concrete strategy for exploring the possibilities of big data for official statistics, by means of the Big Data Roadmap and Action Plan 1.0. This is an important first step and will have a significant influence on implementing the concept of big data inside the statistical offices of Germany.

Statistical Analyses and Modeling of the Implementation of Agile Manufacturing Tactics in Industrial Firms

Directory of Open Access Journals (Sweden)

Mohammad D. AL-Tahat

2012-01-01

Full Text Available This paper provides a review and introduction on agile manufacturing. Tactics of agile manufacturing are mapped into different production areas (eight-construct latent: manufacturing equipment and technology, processes technology and know-how, quality and productivity improvement, production planning and control, shop floor management, product design and development, supplier relationship management, and customer relationship management. The implementation level of agile manufacturing tactics is investigated in each area. A structural equation model is proposed. Hypotheses are formulated. Feedback from 456 firms is collected using five-point-Likert-scale questionnaire. Statistical analysis is carried out using IBM SPSS and AMOS. Multicollinearity, content validity, consistency, construct validity, ANOVA analysis, and relationships between agile components are tested. The results of this study prove that the agile manufacturing tactics have positive effect on the overall agility level. This conclusion can be used by manufacturing firms to manage challenges when trying to be agile.

Shear Bond Strengths and Morphological Evaluation of Filled and Unfilled Adhesive Interfaces to Enamel and Dentine

Science.gov (United States)

Mortazavi, Vajihesadat; Fathi, Mohammadhosein; Ataei, Ebrahim; Khodaeian, Niloufar; Askari, Navid

2012-01-01

In this laboratory study shear bond strengths of three filled and one unfilled adhesive systems to enamel and dentine were compared. Forty-eight extracted intact noncarious human mandibular molars were randomly assigned to two groups of 24 one for bonding to enamel and the other for bonding to dentine. Buccal and lingual surfaces of each tooth were randomly assigned for application of each one of filled (Prime & Bond NT (PBNT), Optibond Solo Plus (OBSP), and Clearfil SE Bond (CSEB)) and unfilled (Single Bond (SB)) adhesive systems (n = 12). A universal resin composite was placed into the translucent plastic cylinders (3 mm in diameter and 2 mm in length) and seated against the enamel and dentine surfaces and polymerized for 40 seconds. Shear bond strength was determined using a universal testing machine, and the results were statistically analyzed using two-way ANOVA, one-way ANOVA, t-test, and Tukey HSD post hoc test with a 5% level of significance.There were no statistically significant differences in bond strength between the adhesive systems in enamel, but CSEB and SB exhibited significantly higher and lower bond strength to dentine, respectively, than the other tested adhesive systems while there were no statistically significant differences between PBNT and OBSP. PMID:23209471

Shear Bond Strengths and Morphological Evaluation of Filled and Unfilled Adhesive Interfaces to Enamel and Dentine

Directory of Open Access Journals (Sweden)

Vajihesadat Mortazavi

2012-01-01

Full Text Available In this laboratory study shear bond strengths of three filled and one unfilled adhesive systems to enamel and dentine were compared. Forty-eight extracted intact noncarious human mandibular molars were randomly assigned to two groups of 24 one for bonding to enamel and the other for bonding to dentine. Buccal and lingual surfaces of each tooth were randomly assigned for application of each one of filled (Prime & Bond NT (PBNT, Optibond Solo Plus (OBSP, and Clearfil SE Bond (CSEB and unfilled (Single Bond (SB adhesive systems (n=12. A universal resin composite was placed into the translucent plastic cylinders (3 mm in diameter and 2 mm in length and seated against the enamel and dentine surfaces and polymerized for 40 seconds. Shear bond strength was determined using a universal testing machine, and the results were statistically analyzed using two-way ANOVA, one-way ANOVA, t-test, and Tukey HSD post hoc test with a 5% level of significance.There were no statistically significant differences in bond strength between the adhesive systems in enamel, but CSEB and SB exhibited significantly higher and lower bond strength to dentine, respectively, than the other tested adhesive systems while there were no statistically significant differences between PBNT and OBSP.

Wheat crown rot pathogens Fusarium graminearum and F. pseudograminearum lack specialization.

Science.gov (United States)

Chakraborty, Sukumar; Obanor, Friday; Westecott, Rhyannyn; Abeywickrama, Krishanthi

2010-10-01

This article reports a lack of pathogenic specialization among Australian Fusarium graminearum and F. pseudograminearum causing crown rot (CR) of wheat using analysis of variance (ANOVA), principal component and biplot analysis, Kendall's coefficient of concordance (W), and κ statistics. Overall, F. pseudograminearum was more aggressive than F. graminearum, supporting earlier delineation of the crown-infecting group as a new species. Although significant wheat line-pathogen isolate interaction in ANOVA suggested putative specialization when seedlings of 60 wheat lines were inoculated with 4 pathogen isolates or 26 wheat lines were inoculated with 10 isolates, significant W and κ showed agreement in rank order of wheat lines, indicating a lack of specialization. The first principal component representing nondifferential aggressiveness explained a large part (up to 65%) of the variation in CR severity. The differential components were small and more pronounced in seedlings than in adult plants. By maximizing variance on the first two principal components, biplots were useful for highlighting the association between isolates and wheat lines. A key finding of this work is that a range of analytical tools are needed to explore pathogenic specialization, and a statistically significant interaction in an ANOVA cannot be taken as conclusive evidence of specialization. With no highly resistant wheat cultivars, Fusarium isolates mostly differ in aggressiveness; however, specialization may appear as more resistant cultivars become widespread.

Optimization of Parameters for Manufacture Nanopowder Bioceramics at Machine Pulverisette 6 by Taguchi and ANOVA Method

Science.gov (United States)

Van Hoten, Hendri; Gunawarman; Mulyadi, Ismet Hari; Kurniawan Mainil, Afdhal; Putra, Bismantoloa dan

2018-02-01

This research is about manufacture nanopowder Bioceramics from local materials used Ball Milling for biomedical applications. Source materials for the manufacture of medicines are plants, animal tissues, microbial structures and engineering biomaterial. The form of raw material medicines is a powder before mixed. In the case of medicines, research is to find sources of biomedical materials that will be in the nanoscale powders can be used as raw material for medicine. One of the biomedical materials that can be used as raw material for medicine is of the type of bioceramics is chicken eggshells. This research will develop methods for manufacture nanopowder material from chicken eggshells with Ball Milling using the Taguchi method and ANOVA. Eggshell milled using a variation of Milling rate on 150, 200 and 250 rpm, the time variation of 1, 2 and 3 hours and variations the grinding balls to eggshell powder weight ratio (BPR) 1: 6, 1: 8, 1: 10. Before milled with Ball Milling crushed eggshells in advance and calcinate to a temperature of 900°C. After the milled material characterization of the fine powder of eggshell using SEM to see its size. The result of this research is optimum parameter of Taguchi Design analysis that is 250 rpm milling rate, 3 hours milling time and BPR is 1: 6 with the average eggshell powder size is 1.305 μm. Milling speed, milling time and ball to powder weight of ratio have contribution successively equal to 60.82%, 30.76% and 6.64% by error equal to 1.78%.

National Statistical Commission and Indian Official Statistics*

Indian Academy of Sciences (India)

IAS Admin

a good collection of official statistics of that time. With more .... statistical agencies and institutions to provide details of statistical activities .... ing several training programmes. .... ful completion of Indian Statistical Service examinations, the.

Race, Socioeconomic Status, and Implicit Bias: Implications for Closing the Achievement Gap

Science.gov (United States)

Schlosser, Elizabeth Auretta Cox

This study accessed the relationship between race, socioeconomic status, age and the race implicit bias held by middle and high school science teachers in Mobile and Baldwin County Public School Systems. Seventy-nine participants were administered the race Implicit Association Test (race IAT), created by Greenwald, A. G., Nosek, B. A., & Banaji, M. R., (2003) and a demographic survey. Quantitative analysis using analysis of variances, ANOVA and t-tests were used in this study. An ANOVA was performed comparing the race IAT scores of African American science teachers and their Caucasian counterparts. A statically significant difference was found (F = .4.56, p = .01). An ANOVA was also performed using the race IAT scores comparing the age of the participants; the analysis yielded no statistical difference based on age. A t-test was performed comparing the race IAT scores of African American teachers who taught at either Title I or non-Title I schools; no statistical difference was found between groups (t = -17.985, p .001). This research examines the implications of the achievement gap among African American and Caucasian students in science.

Official Statistics and Statistics Education: Bridging the Gap

Directory of Open Access Journals (Sweden)

Gal Iddo

2017-03-01

Full Text Available This article aims to challenge official statistics providers and statistics educators to ponder on how to help non-specialist adult users of statistics develop those aspects of statistical literacy that pertain to official statistics. We first document the gap in the literature in terms of the conceptual basis and educational materials needed for such an undertaking. We then review skills and competencies that may help adults to make sense of statistical information in areas of importance to society. Based on this review, we identify six elements related to official statistics about which non-specialist adult users should possess knowledge in order to be considered literate in official statistics: (1 the system of official statistics and its work principles; (2 the nature of statistics about society; (3 indicators; (4 statistical techniques and big ideas; (5 research methods and data sources; and (6 awareness and skills for citizens’ access to statistical reports. Based on this ad hoc typology, we discuss directions that official statistics providers, in cooperation with statistics educators, could take in order to (1 advance the conceptualization of skills needed to understand official statistics, and (2 expand educational activities and services, specifically by developing a collaborative digital textbook and a modular online course, to improve public capacity for understanding of official statistics.

A comparative analysis of badminton game instructions effect of non ...

African Journals Online (AJOL)

... drop shot and smash in doubles game play, ANCOVA and ANOVA statistics indicated significant improved performance via NP compared to LP. Conclusion, implementing NP in schools would further strengthen TGfU as teachers can adjust tactics, skill tasks to the performer's abilities and situated learning environment.

Factors Influencing Stress, Burnout, and Retention of Secondary Teachers

Science.gov (United States)

Fisher, Molly H.

2011-01-01

This study examines the stress, burnout, satisfaction, and preventive coping skills of nearly 400 secondary teachers to determine variables contributing to these major factors influencing teachers. Analysis of Variance (ANOVA) statistics were conducted that found the burnout levels between new and experienced teachers are significantly different,…

Assessment of Social Anxiety and Its Correlates among ...

African Journals Online (AJOL)

Statistical analysis, using Regression Analysis and Four-Way ANOVA, revealed that while some factors predicted social anxiety (such as dating anxiety and fear of negative evaluation); Self esteem, Social maladjustment and assertiveness did not. Also demographic variables did not have any significant effect on social ...

Arsenic health risk assessment in drinking water and source apportionment using multivariate statistical techniques in Kohistan region, northern Pakistan.

Science.gov (United States)

Muhammad, Said; Tahir Shah, M; Khan, Sardar

2010-10-01

The present study was conducted in Kohistan region, where mafic and ultramafic rocks (Kohistan island arc and Indus suture zone) and metasedimentary rocks (Indian plate) are exposed. Water samples were collected from the springs, streams and Indus river and analyzed for physical parameters, anions, cations and arsenic (As(3+), As(5+) and arsenic total). The water quality in Kohistan region was evaluated by comparing the physio-chemical parameters with permissible limits set by Pakistan environmental protection agency and world health organization. Most of the studied parameters were found within their respective permissible limits. However in some samples, the iron and arsenic concentrations exceeded their permissible limits. For health risk assessment of arsenic, the average daily dose, hazards quotient (HQ) and cancer risk were calculated by using statistical formulas. The values of HQ were found >1 in the samples collected from Jabba, Dubair, while HQ values were pollution load was also calculated by using multivariate statistical techniques like one-way ANOVA, correlation analysis, regression analysis, cluster analysis and principle component analysis. Copyright © 2010 Elsevier Ltd. All rights reserved.

Development of free statistical software enabling researchers to calculate confidence levels, clinical significance curves and risk-benefit contours

International Nuclear Information System (INIS)

Shakespeare, T.P.; Mukherjee, R.K.; Gebski, V.J.

2003-01-01

Confidence levels, clinical significance curves, and risk-benefit contours are tools improving analysis of clinical studies and minimizing misinterpretation of published results, however no software has been available for their calculation. The objective was to develop software to help clinicians utilize these tools. Excel 2000 spreadsheets were designed using only built-in functions, without macros. The workbook was protected and encrypted so that users can modify only input cells. The workbook has 4 spreadsheets for use in studies comparing two patient groups. Sheet 1 comprises instructions and graphic examples for use. Sheet 2 allows the user to input the main study results (e.g. survival rates) into a 2-by-2 table. Confidence intervals (95%), p-value and the confidence level for Treatment A being better than Treatment B are automatically generated. An additional input cell allows the user to determine the confidence associated with a specified level of benefit. For example if the user wishes to know the confidence that Treatment A is at least 10% better than B, 10% is entered. Sheet 2 automatically displays clinical significance curves, graphically illustrating confidence levels for all possible benefits of one treatment over the other. Sheet 3 allows input of toxicity data, and calculates the confidence that one treatment is more toxic than the other. It also determines the confidence that the relative toxicity of the most effective arm does not exceed user-defined tolerability. Sheet 4 automatically calculates risk-benefit contours, displaying the confidence associated with a specified scenario of minimum benefit and maximum risk of one treatment arm over the other. The spreadsheet is freely downloadable at www.ontumor.com/professional/statistics.htm A simple, self-explanatory, freely available spreadsheet calculator was developed using Excel 2000. The incorporated decision-making tools can be used for data analysis and improve the reporting of results of any

THE ROLE OF GENDER IN READING COMPREHENSION: AN ANALYSIS OF COLLEGE-LEVEL EFL STUDENTS’ COMPREHENSION OF DIFFERENT GENRES

Directory of Open Access Journals (Sweden)

Didem Koban Koç

2016-07-01

Full Text Available The purpose of the present study is to examine the effects of gender on comprehending different types of genre. The study involved 60 first year college students (30 males and 30 females who were taking an advanced reading course at a government university in Turkey. The students were given three reading passages of different genres such as historical fiction, essay and fantasy and were asked to answer comprehension questions related to the passages. Descriptives statistics, one-way ANOVA and repeated measures ANOVA were employed to analyse the relationship between gender and the test scores for each text type. The results showed that (1 the participants, in general, were significantly better at understanding the essay than historical fiction and fantasy (2 there was not a statistically significant difference between males and females regarding comprehending the different types of genres (3 both the male and female participants were significantly better at understanding the essay than historical fiction and fantasy. The study offers suggestions regarding incorporating different types of genre in the classroom.

Association Between Selenium and Malondialdehyde as an Efficient Biomarker of Oxidative Stress in Infantile Cardiac Surgery.

Science.gov (United States)

de Oliveira Ulbrecht, Marlice Oliveira; Gonçalves, Daniel Araujo; Zanoni, Lourdes Zélia Garcia; do Nascimento, Valter Aragão

2018-05-12

The present work describes a method to quantify the level of oxidative stress in infantile cardiac surgery. Fifteen patients, 6 girls and 9 boys, aged between 3 months and 16 years were divided into three groups. The first group sought to quantify the oxidative stress from differing concentrations of selenium. The second group used malondialdehyde as an indicator of oxidative stress. Finally, the third group quantified oxidative stress by normalizing the selenium concentration via malondialdehyde. Blood aliquots of 1.50 ml, drawn from the radial artery, were collected and centrifuged for quantification of Se and MDA in plasma. The statistical method ANOVA was used with a 95% confidence interval to indicate significant statistical differences between the post- and pre-operative stage for each group. The concentrations of malondialdehyde were measured by using UV-Vis following the thiobarbituric acid reaction method. For quantification of selenium, the samples were submitted to assisted microwave digestion and measured by ICP OES. In the first two groups, it was not possible to affirm that selenium and malondialdehyde could be biomarkers of oxidative stress, so a statistic test (ANOVA) was performed. However, the selenium/malondialdehyde ratios in the pre-operative and post-operative stage were 2.10 ± 0.70 and 3.20 ± 0.40, respectively. The ANOVA test confirmed a statistically significant difference between the pre- and post-operative stages with p value = 0.004. Here, the ratio of selenium concentration by malondialdehyde was confirmed to be an effective parameter for demonstration and quantification of oxidative stress activity at the post-operative stage.

Review of the Statistical Techniques in Medical Sciences | Okeh ...

African Journals Online (AJOL)

... medical researcher in selecting the appropriate statistical techniques. Of course, all statistical techniques have certain underlying assumptions, which must be checked before the technique is applied. Keywords: Variable, Prospective Studies, Retrospective Studies, Statistical significance. Bio-Research Vol. 6 (1) 2008: pp.

Which statistics should tropical biologists learn?

Directory of Open Access Journals (Sweden)

Natalia Loaiza Velásquez

2011-09-01

Full Text Available Tropical biologists study the richest and most endangered biodiversity in the planet, and in these times of climate change and mega-extinctions, the need for efficient, good quality research is more pressing than in the past. However, the statistical component in research published by tropical authors sometimes suffers from poor quality in data collection; mediocre or bad experimental design and a rigid and outdated view of data analysis. To suggest improvements in their statistical education, we listed all the statistical tests and other quantitative analyses used in two leading tropical journals, the Revista de Biología Tropical and Biotropica, during a year. The 12 most frequent tests in the articles were: Analysis of Variance (ANOVA, Chi-Square Test, Student’s T Test, Linear Regression, Pearson’s Correlation Coefficient, Mann-Whitney U Test, Kruskal-Wallis Test, Shannon’s Diversity Index, Tukey’s Test, Cluster Analysis, Spearman’s Rank Correlation Test and Principal Component Analysis. We conclude that statistical education for tropical biologists must abandon the old syllabus based on the mathematical side of statistics and concentrate on the correct selection of these and other procedures and tests, on their biological interpretation and on the use of reliable and friendly freeware. We think that their time will be better spent understanding and protecting tropical ecosystems than trying to learn the mathematical foundations of statistics: in most cases, a well designed one-semester course should be enough for their basic requirements. Rev. Biol. Trop. 59 (3: 983-992. Epub 2011 September 01.Los biólogos tropicales estudian la biodiversidad más rica y amenazada del planeta, y en estos tiempos de cambio climático y mega-extinción, la necesidad de investigación de buena calidad es más acuciante que en el pasado. Sin embargo, el componente estadístico en la investigación publicada por los autores tropicales adolece a veces

An in vivo assessment of the influence of needle gauges on endodontic irrigation flow rate.

Science.gov (United States)

Gopikrishna, Velayutham; Sibi, Swamy; Archana, Durvasulu; Pradeep Kumar, Angabakkam Rajasekaran; Narayanan, Lakshmi

2016-01-01

The aim of this clinical study was to assess the influence of irrigation needle gauge on endodontic irrigation flow rates. In vivo assessment. Five specialist endodontists performed intracanal irrigation procedures on 50 mesiobuccal canal of mandibular first molars using three different irrigation needle gauges. Data of time taken for irrigation was recorded by an irrigation testing system and analyzed using independent sample "T" test and one-way analysis of variance (ANOVA) test. The level of significance was set at P < 0.05. The following tests were used for the statistical analysis: Independent sample "T" test, one-way ANOVA test, and post hoc multiple comparison was carried out using Tukey's honest significant difference (HSD) test using Statistical Package for the Social Sciences (SPSS) version 16 for Windows. The average flow rate of 26 gauge was 0.27 mLs(-1), of 27 gauge was 0.19 mLs(-1), and of 30 gauge was 0.09 mls(-1). There was statistical significance among the gauges (P < 0.001). 26 gauge had highest flow rate when compared with other groups followed by 27 gauge and 30 gauge respectively. The operator variability for flow rate of three endodontic irrigation needle gauges (26 gauge, 27 gauge, and 30 gauge) was found to be not significant. Needle gauge has significant influence on endodontic irrigation flow rate.

Sample Size and Statistical Conclusions from Tests of Fit to the Rasch Model According to the Rasch Unidimensional Measurement Model (Rumm) Program in Health Outcome Measurement.

Science.gov (United States)

Hagell, Peter; Westergren, Albert

Sample size is a major factor in statistical null hypothesis testing, which is the basis for many approaches to testing Rasch model fit. Few sample size recommendations for testing fit to the Rasch model concern the Rasch Unidimensional Measurement Models (RUMM) software, which features chi-square and ANOVA/F-ratio based fit statistics, including Bonferroni and algebraic sample size adjustments. This paper explores the occurrence of Type I errors with RUMM fit statistics, and the effects of algebraic sample size adjustments. Data with simulated Rasch model fitting 25-item dichotomous scales and sample sizes ranging from N = 50 to N = 2500 were analysed with and without algebraically adjusted sample sizes. Results suggest the occurrence of Type I errors with N less then or equal to 500, and that Bonferroni correction as well as downward algebraic sample size adjustment are useful to avoid such errors, whereas upward adjustment of smaller samples falsely signal misfit. Our observations suggest that sample sizes around N = 250 to N = 500 may provide a good balance for the statistical interpretation of the RUMM fit statistics studied here with respect to Type I errors and under the assumption of Rasch model fit within the examined frame of reference (i.e., about 25 item parameters well targeted to the sample).

Spectral and cross-spectral analysis of uneven time series with the smoothed Lomb-Scargle periodogram and Monte Carlo evaluation of statistical significance

Science.gov (United States)

Pardo-Igúzquiza, Eulogio; Rodríguez-Tovar, Francisco J.

2012-12-01

Many spectral analysis techniques have been designed assuming sequences taken with a constant sampling interval. However, there are empirical time series in the geosciences (sediment cores, fossil abundance data, isotope analysis, …) that do not follow regular sampling because of missing data, gapped data, random sampling or incomplete sequences, among other reasons. In general, interpolating an uneven series in order to obtain a succession with a constant sampling interval alters the spectral content of the series. In such cases it is preferable to follow an approach that works with the uneven data directly, avoiding the need for an explicit interpolation step. The Lomb-Scargle periodogram is a popular choice in such circumstances, as there are programs available in the public domain for its computation. One new computer program for spectral analysis improves the standard Lomb-Scargle periodogram approach in two ways: (1) It explicitly adjusts the statistical significance to any bias introduced by variance reduction smoothing, and (2) it uses a permutation test to evaluate confidence levels, which is better suited than parametric methods when neighbouring frequencies are highly correlated. Another novel program for cross-spectral analysis offers the advantage of estimating the Lomb-Scargle cross-periodogram of two uneven time series defined on the same interval, and it evaluates the confidence levels of the estimated cross-spectra by a non-parametric computer intensive permutation test. Thus, the cross-spectrum, the squared coherence spectrum, the phase spectrum, and the Monte Carlo statistical significance of the cross-spectrum and the squared-coherence spectrum can be obtained. Both of the programs are written in ANSI Fortran 77, in view of its simplicity and compatibility. The program code is of public domain, provided on the website of the journal (http://www.iamg.org/index.php/publisher/articleview/frmArticleID/112/). Different examples (with simulated and

A hybrid approach to select features and classify diseases based on medical data

Science.gov (United States)

AbdelLatif, Hisham; Luo, Jiawei

2018-03-01

Feature selection is popular problem in the classification of diseases in clinical medicine. Here, we developing a hybrid methodology to classify diseases, based on three medical datasets, Arrhythmia, Breast cancer, and Hepatitis datasets. This methodology called k-means ANOVA Support Vector Machine (K-ANOVA-SVM) uses K-means cluster with ANOVA statistical to preprocessing data and selection the significant features, and Support Vector Machines in the classification process. To compare and evaluate the performance, we choice three classification algorithms, decision tree Naïve Bayes, Support Vector Machines and applied the medical datasets direct to these algorithms. Our methodology was a much better classification accuracy is given of 98% in Arrhythmia datasets, 92% in Breast cancer datasets and 88% in Hepatitis datasets, Compare to use the medical data directly with decision tree Naïve Bayes, and Support Vector Machines. Also, the ROC curve and precision with (K-ANOVA-SVM) Achieved best results than other algorithms

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach.

Science.gov (United States)

Park, Jihong; Seeley, Matthew K; Francom, Devin; Reese, C Shane; Hopkins, J Ty

2017-12-01

In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle, knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. When using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function.

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach

Directory of Open Access Journals (Sweden)

Park Jihong

2017-12-01

Full Text Available In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle, knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01 and hip joint angle (F1,18 = 5.77, p = 0.03, but did not for the knee joint angle (F1,18 = 0.36, p = 0.56. The functional data analysis, however, found several differences at initial contact (ankle and knee joint, in the mid-stance (each joint and at toe off (ankle. Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. When using the functional data analysis approach, a researcher can (1 evaluate the entire data as a function, and (2 detect the location and magnitude of differences within the evaluated function.

Statistical thermodynamics

International Nuclear Information System (INIS)

Lim, Gyeong Hui

2008-03-01

This book consists of 15 chapters, which are basic conception and meaning of statistical thermodynamics, Maxwell-Boltzmann's statistics, ensemble, thermodynamics function and fluctuation, statistical dynamics with independent particle system, ideal molecular system, chemical equilibrium and chemical reaction rate in ideal gas mixture, classical statistical thermodynamics, ideal lattice model, lattice statistics and nonideal lattice model, imperfect gas theory on liquid, theory on solution, statistical thermodynamics of interface, statistical thermodynamics of a high molecule system and quantum statistics

[Statistics for statistics?--Thoughts about psychological tools].

Science.gov (United States)

Berger, Uwe; Stöbel-Richter, Yve

2007-12-01

Statistical methods take a prominent place among psychologists' educational programs. Being known as difficult to understand and heavy to learn, students fear of these contents. Those, who do not aspire after a research carrier at the university, will forget the drilled contents fast. Furthermore, because it does not apply for the work with patients and other target groups at a first glance, the methodological education as a whole was often questioned. For many psychological practitioners the statistical education makes only sense by enforcing respect against other professions, namely physicians. For the own business, statistics is rarely taken seriously as a professional tool. The reason seems to be clear: Statistics treats numbers, while psychotherapy treats subjects. So, does statistics ends in itself? With this article, we try to answer the question, if and how statistical methods were represented within the psychotherapeutical and psychological research. Therefore, we analyzed 46 Originals of a complete volume of the journal Psychotherapy, Psychosomatics, Psychological Medicine (PPmP). Within the volume, 28 different analyse methods were applied, from which 89 per cent were directly based upon statistics. To be able to write and critically read Originals as a backbone of research, presumes a high degree of statistical education. To ignore statistics means to ignore research and at least to reveal the own professional work to arbitrariness.

Deconstruction of Oncogenic K-RAS Signaling Reveals Focal Adhesion Kinase as a Novel Therapeutic Target in NSCLC

Science.gov (United States)

2016-12-01

using the log-rank test using SPSS Statistics 17.0. One-way ANOVA followed by Tukey post hoc test was used to compare the pathologic stage among groups... Statistical analyses All data presented are the average standard deviations of experiments repeated three ormore times. Significance was deter- mined using ...understood [27]. Using single nucleotide polymorphism (SNPs) data, we discovered that PIAS1 and FAK are frequently co-amplified in lung cancer specimens. We

Promotional Strategy Impacts on Organizational Market Share and Profitability

OpenAIRE

Adesoga Dada Adefulu

2015-01-01

The paper examined promotional strategy impacts on market share and profitability in Coca-Cola and 7up companies in Lagos State, Nigeria. Survey research method was adopted. The study population was the staff in marketing positions in the selected companies. Questionnaire was administered on the samples from Coca-Cola and 7UP companies. The statistical tool employed was the univariate analysis of variance (ANOVA) to determine the statistical significance and the extent to which...

Uranium determination in U-Al alloy with statistical tools support

International Nuclear Information System (INIS)

Furusawa, Helio Akira; Medalla, Felipe Quirino; Cotrim, Marycel Elena Barbosa; Pires, Maria Aparecida Faustino

2011-01-01

ICP-OES was used to quantify total uranium in natural UAl x powder alloy. A simple solubilisation procedure using diluted HNO 3 /HCl was successfully applied. Only 100 mg of sample were used which is an advantage over the volumetric methodologies. Only two dilutions were needed to reach measurable concentration. No other treatment was applied to the solutions. Calibration curves of three uranium lines (367.007, 385.958 and 409.014 nm) were evaluated using ANOVA. Comparing the indicators, the 367.007 nm line was the poorer one but exhibiting a R 2 = 0.998 and 0.9996 and 0.999 for the other two lines. No significant difference was found between these two lines. If needed, the 385.958 nm line could be used to quantify uranium in very low concentrations but with few advantages over the 409.014 nm line, if so. The average uranium concentration found was 0.80±0.01 μg.g-1, as expected for a predominant UAl 2 phase alloy. Higher uranium concentrations are also expected to be successfully quantified using these lines. In order to verify possibly inhomogeneity due to the high uranium concentration, one-way ANOVA was applied to 3 replicates. Homogeneity was confirmed measuring in both 385.958 and 409.014 nm lines. The uncertainty of solution homogeneity was estimated also in these two emission lines giving 0.006 and 0.005 μg.g-1, respectively. These two values are in compliance with the standard deviation of the average. (author)

Statistical Optimization for Biobutanol Production by Clostridium acetobutylicum ATCC 824 from Oil Palm Frond (OPF Juice Using Response Surface Methodology

Directory of Open Access Journals (Sweden)

Muhamad Nasrah Nur Syazana

2017-01-01

Full Text Available The interaction between incubation temperature, yeast extract concentration and inoculum size was investigated to optimize critical environmental parameters for production of biobutanol from oil palm frond (OPF juice by Clostridium acetobutylicum ATCC 824 using response surface methodology (RSM. A central composite design (CCD was applied as the experimental design and a polynomial regression model with quadratic term was used to analyse the experimental data using analysis of variance (ANOVA. ANOVA analysis showed that the model was very significant (p < 0.0001 for the biobutanol production. The incubation temperature, yeast extract concentration and inoculum size showed significant value at p < 0.005. The results of optimization process showed that a maximum biobutanol production was obtained under the condition of temperature 37 °C, yeast extract concentration 5.5 g/L and inoculum size 10%. Under these optimized conditions, the highest biobutanol yield was 0.3054 g/g after 144 hours of incubation period. The model was validated by applying the optimized conditions and 0.2992 g/g biobutanol yield was obtained. These experimental findings were in close agreement with the model prediction, with a difference of only 9.76%.

NLO error propagation exercise: statistical results

International Nuclear Information System (INIS)

Pack, D.J.; Downing, D.J.

1985-09-01

Error propagation is the extrapolation and cumulation of uncertainty (variance) above total amounts of special nuclear material, for example, uranium or 235 U, that are present in a defined location at a given time. The uncertainty results from the inevitable inexactness of individual measurements of weight, uranium concentration, 235 U enrichment, etc. The extrapolated and cumulated uncertainty leads directly to quantified limits of error on inventory differences (LEIDs) for such material. The NLO error propagation exercise was planned as a field demonstration of the utilization of statistical error propagation methodology at the Feed Materials Production Center in Fernald, Ohio from April 1 to July 1, 1983 in a single material balance area formed specially for the exercise. Major elements of the error propagation methodology were: variance approximation by Taylor Series expansion; variance cumulation by uncorrelated primary error sources as suggested by Jaech; random effects ANOVA model estimation of variance effects (systematic error); provision for inclusion of process variance in addition to measurement variance; and exclusion of static material. The methodology was applied to material balance area transactions from the indicated time period through a FORTRAN computer code developed specifically for this purpose on the NLO HP-3000 computer. This paper contains a complete description of the error propagation methodology and a full summary of the numerical results of applying the methodlogy in the field demonstration. The error propagation LEIDs did encompass the actual uranium and 235 U inventory differences. Further, one can see that error propagation actually provides guidance for reducing inventory differences and LEIDs in future time periods

On a curvature-statistics theorem

International Nuclear Information System (INIS)

Calixto, M; Aldaya, V

2008-01-01

The spin-statistics theorem in quantum field theory relates the spin of a particle to the statistics obeyed by that particle. Here we investigate an interesting correspondence or connection between curvature (κ = ±1) and quantum statistics (Fermi-Dirac and Bose-Einstein, respectively). The interrelation between both concepts is established through vacuum coherent configurations of zero modes in quantum field theory on the compact O(3) and noncompact O(2; 1) (spatial) isometry subgroups of de Sitter and Anti de Sitter spaces, respectively. The high frequency limit, is retrieved as a (zero curvature) group contraction to the Newton-Hooke (harmonic oscillator) group. We also make some comments on the physical significance of the vacuum energy density and the cosmological constant problem.

On a curvature-statistics theorem

Energy Technology Data Exchange (ETDEWEB)

Calixto, M [Departamento de Matematica Aplicada y Estadistica, Universidad Politecnica de Cartagena, Paseo Alfonso XIII 56, 30203 Cartagena (Spain); Aldaya, V [Instituto de Astrofisica de Andalucia, Apartado Postal 3004, 18080 Granada (Spain)], E-mail: Manuel.Calixto@upct.es

2008-08-15

The spin-statistics theorem in quantum field theory relates the spin of a particle to the statistics obeyed by that particle. Here we investigate an interesting correspondence or connection between curvature ({kappa} = {+-}1) and quantum statistics (Fermi-Dirac and Bose-Einstein, respectively). The interrelation between both concepts is established through vacuum coherent configurations of zero modes in quantum field theory on the compact O(3) and noncompact O(2; 1) (spatial) isometry subgroups of de Sitter and Anti de Sitter spaces, respectively. The high frequency limit, is retrieved as a (zero curvature) group contraction to the Newton-Hooke (harmonic oscillator) group. We also make some comments on the physical significance of the vacuum energy density and the cosmological constant problem.

Child Sustained Attention in Preschool-Age Children

Science.gov (United States)

DiCarlo, Cynthia F.; Baumgartner, Jennifer J.; Ota, Carrie; Geary, Kelly

2016-01-01

This study examined the mean duration of child attention across three teaching conditions (child choice, adult choice, or adult presentation) of 63 preschool-age children. A repeated-measures ANOVA was used to compare the means across the three teaching conditions, indicating a statistically significant difference between the teaching conditions.…

Testing statistical hypotheses of equivalence

CERN Document Server

Wellek, Stefan

2010-01-01

Equivalence testing has grown significantly in importance over the last two decades, especially as its relevance to a variety of applications has become understood. Yet published work on the general methodology remains scattered in specialists' journals, and for the most part, it focuses on the relatively narrow topic of bioequivalence assessment.With a far broader perspective, Testing Statistical Hypotheses of Equivalence provides the first comprehensive treatment of statistical equivalence testing. The author addresses a spectrum of specific, two-sided equivalence testing problems, from the

Calculating statistical distributions from operator relations: The statistical distributions of various intermediate statistics

International Nuclear Information System (INIS)

Dai, Wu-Sheng; Xie, Mi

2013-01-01

In this paper, we give a general discussion on the calculation of the statistical distribution from a given operator relation of creation, annihilation, and number operators. Our result shows that as long as the relation between the number operator and the creation and annihilation operators can be expressed as a † b=Λ(N) or N=Λ −1 (a † b), where N, a † , and b denote the number, creation, and annihilation operators, i.e., N is a function of quadratic product of the creation and annihilation operators, the corresponding statistical distribution is the Gentile distribution, a statistical distribution in which the maximum occupation number is an arbitrary integer. As examples, we discuss the statistical distributions corresponding to various operator relations. In particular, besides the Bose–Einstein and Fermi–Dirac cases, we discuss the statistical distributions for various schemes of intermediate statistics, especially various q-deformation schemes. Our result shows that the statistical distributions corresponding to various q-deformation schemes are various Gentile distributions with different maximum occupation numbers which are determined by the deformation parameter q. This result shows that the results given in much literature on the q-deformation distribution are inaccurate or incomplete. -- Highlights: ► A general discussion on calculating statistical distribution from relations of creation, annihilation, and number operators. ► A systemic study on the statistical distributions corresponding to various q-deformation schemes. ► Arguing that many results of q-deformation distributions in literature are inaccurate or incomplete

Statistical and theoretical research

International Nuclear Information System (INIS)

Anon.

1983-01-01

Significant accomplishments include the creation of field designs to detect population impacts, new census procedures for small mammals, and methods for designing studies to determine where and how much of a contaminant is extent over certain landscapes. A book describing these statistical methods is currently being written and will apply to a variety of environmental contaminants, including radionuclides. PNL scientists also have devised an analytical method for predicting the success of field eexperiments on wild populations. Two highlights of current research are the discoveries that population of free-roaming horse herds can double in four years and that grizzly bear populations may be substantially smaller than once thought. As stray horses become a public nuisance at DOE and other large Federal sites, it is important to determine their number. Similar statistical theory can be readily applied to other situations where wild animals are a problem of concern to other government agencies. Another book, on statistical aspects of radionuclide studies, is written specifically for researchers in radioecology

Significance analysis of lexical bias in microarray data

Directory of Open Access Journals (Sweden)

Falkow Stanley

2003-04-01

Full Text Available Abstract Background Genes that are determined to be significantly differentially regulated in microarray analyses often appear to have functional commonalities, such as being components of the same biochemical pathway. This results in certain words being under- or overrepresented in the list of genes. Distinguishing between biologically meaningful trends and artifacts of annotation and analysis procedures is of the utmost importance, as only true biological trends are of interest for further experimentation. A number of sophisticated methods for identification of significant lexical trends are currently available, but these methods are generally too cumbersome for practical use by most microarray users. Results We have developed a tool, LACK, for calculating the statistical significance of apparent lexical bias in microarray datasets. The frequency of a user-specified list of search terms in a list of genes which are differentially regulated is assessed for statistical significance by comparison to randomly generated datasets. The simplicity of the input files and user interface targets the average microarray user who wishes to have a statistical measure of apparent lexical trends in analyzed datasets without the need for bioinformatics skills. The software is available as Perl source or a Windows executable. Conclusion We have used LACK in our laboratory to generate biological hypotheses based on our microarray data. We demonstrate the program's utility using an example in which we confirm significant upregulation of SPI-2 pathogenicity island of Salmonella enterica serovar Typhimurium by the cation chelator dipyridyl.

The statistical geoportal and the ``cartographic added value'' - creation of the spatial knowledge infrastructure

Science.gov (United States)

Fiedukowicz, Anna; Gasiorowski, Jedrzej; Kowalski, Paweł; Olszewski, Robert; Pillich-Kolipinska, Agata

2012-11-01

The wide access to source data, published by numerous websites, results in situation, when information acquisition is not a problem any more. The real problem is how to transform information in the useful knowledge. Cartographic method of research, dealing with spatial data, has been serving this purpose for many years. Nowadays, it allows conducting analyses at the high complexity level, thanks to the intense development in IT technologies, The vast majority of analytic methods utilizing the so-called data mining and data enrichment techniques, however, concerns non-spatial data. According to the Authors, utilizing those techniques in spatial data analysis (including analysis based on statistical data with spatial reference), would allow the evolution of the Spatial Information Infrastructure (SII) into the Spatial Knowledge Infrastructure (SKI). The SKI development would benefit from the existence of statistical geoportal. Its proposed functionality, consisting of data analysis as well as visualization, is outlined in the article. The examples of geostatistical analyses (ANOVA and the regression model considering the spatial neighborhood), possible to implement in such portal and allowing to produce the “cartographic added value”, are also presented here. Szeroki dostep do danych zródłowych publikowanych w licznych serwisach internetowych sprawia, iz współczesnie problemem jest nie pozyskanie informacji, lecz umiejetne przekształcenie jej w uzyteczna wiedze. Kartograficzna metoda badan, która od wielu lat słuzy temu celowi w odniesieniu do danych przestrzennych, zyskuje dzis nowe oblicze - pozwala na wykonywanie złozonych analiz dzieki wykorzystaniu intensywnego rozwoju technologii informatycznych. Znaczaca wiekszosc zastosowan metod analitycznych tzw. eksploracyjnej analizy danych (data mining) i ich "wzbogacania” (data enrichment) dotyczy jednakze danych nieprzestrzennych. Wykorzystanie tych metod do analizy danych o charakterze przestrzennym, w

Whither Statistics Education Research?

Science.gov (United States)

Watson, Jane

2016-01-01

This year marks the 25th anniversary of the publication of a "National Statement on Mathematics for Australian Schools", which was the first curriculum statement this country had including "Chance and Data" as a significant component. It is hence an opportune time to survey the history of the related statistics education…

Statistics

CERN Document Server

Hayslett, H T

1991-01-01

Statistics covers the basic principles of Statistics. The book starts by tackling the importance and the two kinds of statistics; the presentation of sample data; the definition, illustration and explanation of several measures of location; and the measures of variation. The text then discusses elementary probability, the normal distribution and the normal approximation to the binomial. Testing of statistical hypotheses and tests of hypotheses about the theoretical proportion of successes in a binomial population and about the theoretical mean of a normal population are explained. The text the

Application of scl - pbl method to increase quality learning of industrial statistics course in department of industrial engineering pancasila university

Science.gov (United States)

Darmawan, M.; Hidayah, N. Y.

2017-12-01

Currently, there has been a change of new paradigm in the learning model in college, ie from Teacher Centered Learning (TCL) model to Student Centered Learing (SCL). It is generally assumed that the SCL model is better than the TCL model. The Courses of 2nd Industrial Statistics in the Department Industrial Engineering Pancasila University is the subject that belongs to the Basic Engineering group. So far, the applied learning model refers more to the TCL model, and field facts show that the learning outcomes are less satisfactory. Of the three consecutive semesters, ie even semester 2013/2014, 2014/2015, and 2015/2016 obtained grade average is equal to 56.0; 61.1, and 60.5. In the even semester of 2016/2017, Classroom Action Research (CAR) is conducted for this course through the implementation of SCL model with Problem Based Learning (PBL) methods. The hypothesis proposed is that the SCL-PBL model will be able to improve the final grade of the course. The results shows that the average grade of the course can be increased to 73.27. This value was then tested using the ANOVA and the test results concluded that the average grade was significantly different from the average grade value in the previous three semesters.

New scanning technique using Adaptive Statistical Iterative Reconstruction (ASIR) significantly reduced the radiation dose of cardiac CT.

Science.gov (United States)

Tumur, Odgerel; Soon, Kean; Brown, Fraser; Mykytowycz, Marcus

2013-06-01

The aims of our study were to evaluate the effect of application of Adaptive Statistical Iterative Reconstruction (ASIR) algorithm on the radiation dose of coronary computed tomography angiography (CCTA) and its effects on image quality of CCTA and to evaluate the effects of various patient and CT scanning factors on the radiation dose of CCTA. This was a retrospective study that included 347 consecutive patients who underwent CCTA at a tertiary university teaching hospital between 1 July 2009 and 20 September 2011. Analysis was performed comparing patient demographics, scan characteristics, radiation dose and image quality in two groups of patients in whom conventional Filtered Back Projection (FBP) or ASIR was used for image reconstruction. There were 238 patients in the FBP group and 109 patients in the ASIR group. There was no difference between the groups in the use of prospective gating, scan length or tube voltage. In ASIR group, significantly lower tube current was used compared with FBP group, 550 mA (450-600) vs. 650 mA (500-711.25) (median (interquartile range)), respectively, P ASIR group compared with FBP group, 4.29 mSv (2.84-6.02) vs. 5.84 mSv (3.88-8.39) (median (interquartile range)), respectively, P ASIR was associated with increased image noise compared with FBP (39.93 ± 10.22 vs. 37.63 ± 18.79 (mean ± standard deviation), respectively, P ASIR reduces the radiation dose of CCTA without affecting the image quality. © 2013 The Authors. Journal of Medical Imaging and Radiation Oncology © 2013 The Royal Australian and New Zealand College of Radiologists.

Lead uptake of water plants in water stream at Kiteezi landfill site ...

African Journals Online (AJOL)

The concentration of Pb in the samples was measured using the atomic absorption spectrometer (AAS), Perkin Elmer Model. The obtained data was analyzed using descriptive statistics and two-way Anova. The results showed that there was no significant difference (P > 0.05) in the mean Pb content up taken by both plants ...

Industrial commodity statistics yearbook 2001. Production statistics (1992-2001)

International Nuclear Information System (INIS)

2003-01-01

This is the thirty-fifth in a series of annual compilations of statistics on world industry designed to meet both the general demand for information of this kind and the special requirements of the United Nations and related international bodies. Beginning with the 1992 edition, the title of the publication was changed to industrial Commodity Statistics Yearbook as the result of a decision made by the United Nations Statistical Commission at its twenty-seventh session to discontinue, effective 1994, publication of the Industrial Statistics Yearbook, volume I, General Industrial Statistics by the Statistics Division of the United Nations. The United Nations Industrial Development Organization (UNIDO) has become responsible for the collection and dissemination of general industrial statistics while the Statistics Division of the United Nations continues to be responsible for industrial commodity production statistics. The previous title, Industrial Statistics Yearbook, volume II, Commodity Production Statistics, was introduced in the 1982 edition. The first seven editions in this series were published under the title The Growth of World industry and the next eight editions under the title Yearbook of Industrial Statistics. This edition of the Yearbook contains annual quantity data on production of industrial commodities by country, geographical region, economic grouping and for the world. A standard list of about 530 commodities (about 590 statistical series) has been adopted for the publication. The statistics refer to the ten-year period 1992-2001 for about 200 countries and areas

Industrial commodity statistics yearbook 2002. Production statistics (1993-2002)

International Nuclear Information System (INIS)

2004-01-01

This is the thirty-sixth in a series of annual compilations of statistics on world industry designed to meet both the general demand for information of this kind and the special requirements of the United Nations and related international bodies. Beginning with the 1992 edition, the title of the publication was changed to industrial Commodity Statistics Yearbook as the result of a decision made by the United Nations Statistical Commission at its twenty-seventh session to discontinue, effective 1994, publication of the Industrial Statistics Yearbook, volume I, General Industrial Statistics by the Statistics Division of the United Nations. The United Nations Industrial Development Organization (UNIDO) has become responsible for the collection and dissemination of general industrial statistics while the Statistics Division of the United Nations continues to be responsible for industrial commodity production statistics. The previous title, Industrial Statistics Yearbook, volume II, Commodity Production Statistics, was introduced in the 1982 edition. The first seven editions in this series were published under the title 'The Growth of World industry' and the next eight editions under the title 'Yearbook of Industrial Statistics'. This edition of the Yearbook contains annual quantity data on production of industrial commodities by country, geographical region, economic grouping and for the world. A standard list of about 530 commodities (about 590 statistical series) has been adopted for the publication. The statistics refer to the ten-year period 1993-2002 for about 200 countries and areas

Industrial commodity statistics yearbook 2000. Production statistics (1991-2000)

International Nuclear Information System (INIS)

2002-01-01

This is the thirty-third in a series of annual compilations of statistics on world industry designed to meet both the general demand for information of this kind and the special requirements of the United Nations and related international bodies. Beginning with the 1992 edition, the title of the publication was changed to industrial Commodity Statistics Yearbook as the result of a decision made by the United Nations Statistical Commission at its twenty-seventh session to discontinue, effective 1994, publication of the Industrial Statistics Yearbook, volume I, General Industrial Statistics by the Statistics Division of the United Nations. The United Nations Industrial Development Organization (UNIDO) has become responsible for the collection and dissemination of general industrial statistics while the Statistics Division of the United Nations continues to be responsible for industrial commodity production statistics. The previous title, Industrial Statistics Yearbook, volume II, Commodity Production Statistics, was introduced in the 1982 edition. The first seven editions in this series were published under the title The Growth of World industry and the next eight editions under the title Yearbook of Industrial Statistics. This edition of the Yearbook contains annual quantity data on production of industrial commodities by country, geographical region, economic grouping and for the world. A standard list of about 530 commodities (about 590 statistical series) has been adopted for the publication. Most of the statistics refer to the ten-year period 1991-2000 for about 200 countries and areas

Macro-indicators of citation impacts of six prolific countries: InCites data and the statistical significance of trends.

Directory of Open Access Journals (Sweden)

Lutz Bornmann

Full Text Available Using the InCites tool of Thomson Reuters, this study compares normalized citation impact values calculated for China, Japan, France, Germany, United States, and the UK throughout the time period from 1981 to 2010. InCites offers a unique opportunity to study the normalized citation impacts of countries using (i a long publication window (1981 to 2010, (ii a differentiation in (broad or more narrow subject areas, and (iii allowing for the use of statistical procedures in order to obtain an insightful investigation of national citation trends across the years. Using four broad categories, our results show significantly increasing trends in citation impact values for France, the UK, and especially Germany across the last thirty years in all areas. The citation impact of papers from China is still at a relatively low level (mostly below the world average, but the country follows an increasing trend line. The USA exhibits a stable pattern of high citation impact values across the years. With small impact differences between the publication years, the US trend is increasing in engineering and technology but decreasing in medical and health sciences as well as in agricultural sciences. Similar to the USA, Japan follows increasing as well as decreasing trends in different subject areas, but the variability across the years is small. In most of the years, papers from Japan perform below or approximately at the world average in each subject area.

The use of statistical tools in field testing of putative effects of genetically modified plants on nontarget organisms.

Science.gov (United States)

Semenov, Alexander V; Elsas, Jan Dirk; Glandorf, Debora C M; Schilthuizen, Menno; Boer, Willem F

2013-08-01

To fulfill existing guidelines, applicants that aim to place their genetically modified (GM) insect-resistant crop plants on the market are required to provide data from field experiments that address the potential impacts of the GM plants on nontarget organisms (NTO's). Such data may be based on varied experimental designs. The recent EFSA guidance document for environmental risk assessment (2010) does not provide clear and structured suggestions that address the statistics of field trials on effects on NTO's. This review examines existing practices in GM plant field testing such as the way of randomization, replication, and pseudoreplication. Emphasis is placed on the importance of design features used for the field trials in which effects on NTO's are assessed. The importance of statistical power and the positive and negative aspects of various statistical models are discussed. Equivalence and difference testing are compared, and the importance of checking the distribution of experimental data is stressed to decide on the selection of the proper statistical model. While for continuous data (e.g., pH and temperature) classical statistical approaches - for example, analysis of variance (ANOVA) - are appropriate, for discontinuous data (counts) only generalized linear models (GLM) are shown to be efficient. There is no golden rule as to which statistical test is the most appropriate for any experimental situation. In particular, in experiments in which block designs are used and covariates play a role GLMs should be used. Generic advice is offered that will help in both the setting up of field testing and the interpretation and data analysis of the data obtained in this testing. The combination of decision trees and a checklist for field trials, which are provided, will help in the interpretation of the statistical analyses of field trials and to assess whether such analyses were correctly applied. We offer generic advice to risk assessors and applicants that will

Childhood-compared to adolescent-onset bipolar disorder has more statistically significant clinical correlates.

Science.gov (United States)

Holtzman, Jessica N; Miller, Shefali; Hooshmand, Farnaz; Wang, Po W; Chang, Kiki D; Hill, Shelley J; Rasgon, Natalie L; Ketter, Terence A

2015-07-01

The strengths and limitations of considering childhood-and adolescent-onset bipolar disorder (BD) separately versus together remain to be established. We assessed this issue. BD patients referred to the Stanford Bipolar Disorder Clinic during 2000-2011 were assessed with the Systematic Treatment Enhancement Program for BD Affective Disorders Evaluation. Patients with childhood- and adolescent-onset were compared to those with adult-onset for 7 unfavorable bipolar illness characteristics with replicated associations with early-onset patients. Among 502 BD outpatients, those with childhood- (adolescent- (13-18 years, N=218) onset had significantly higher rates for 4/7 unfavorable illness characteristics, including lifetime comorbid anxiety disorder, at least ten lifetime mood episodes, lifetime alcohol use disorder, and prior suicide attempt, than those with adult-onset (>18 years, N=174). Childhood- but not adolescent-onset BD patients also had significantly higher rates of first-degree relative with mood disorder, lifetime substance use disorder, and rapid cycling in the prior year. Patients with pooled childhood/adolescent - compared to adult-onset had significantly higher rates for 5/7 of these unfavorable illness characteristics, while patients with childhood- compared to adolescent-onset had significantly higher rates for 4/7 of these unfavorable illness characteristics. Caucasian, insured, suburban, low substance abuse, American specialty clinic-referred sample limits generalizability. Onset age is based on retrospective recall. Childhood- compared to adolescent-onset BD was more robustly related to unfavorable bipolar illness characteristics, so pooling these groups attenuated such relationships. Further study is warranted to determine the extent to which adolescent-onset BD represents an intermediate phenotype between childhood- and adult-onset BD. Copyright © 2015 Elsevier B.V. All rights reserved.

Encounter Probability of Significant Wave Height

DEFF Research Database (Denmark)

Liu, Z.; Burcharth, H. F.

The determination of the design wave height (often given as the significant wave height) is usually based on statistical analysis of long-term extreme wave height measurement or hindcast. The result of such extreme wave height analysis is often given as the design wave height corresponding to a c...

Statistical evaluation of fatty acid profile and cholesterol content in fish (common carp) lipids obtained by different sample preparation procedures.

Science.gov (United States)

Spiric, Aurelija; Trbovic, Dejana; Vranic, Danijela; Djinovic, Jasna; Petronijevic, Radivoj; Matekalo-Sverak, Vesna

2010-07-05

Studies performed on lipid extraction from animal and fish tissues do not provide information on its influence on fatty acid composition of the extracted lipids as well as on cholesterol content. Data presented in this paper indicate the impact of extraction procedures on fatty acid profile of fish lipids extracted by the modified Soxhlet and ASE (accelerated solvent extraction) procedure. Cholesterol was also determined by direct saponification method, too. Student's paired t-test used for comparison of the total fat content in carp fish population obtained by two extraction methods shows that differences between values of the total fat content determined by ASE and modified Soxhlet method are not statistically significant. Values obtained by three different methods (direct saponification, ASE and modified Soxhlet method), used for determination of cholesterol content in carp, were compared by one-way analysis of variance (ANOVA). The obtained results show that modified Soxhlet method gives results which differ significantly from the results obtained by direct saponification and ASE method. However the results obtained by direct saponification and ASE method do not differ significantly from each other. The highest quantities for cholesterol (37.65 to 65.44 mg/100 g) in the analyzed fish muscle were obtained by applying direct saponification method, as less destructive one, followed by ASE (34.16 to 52.60 mg/100 g) and modified Soxhlet extraction method (10.73 to 30.83 mg/100 g). Modified Soxhlet method for extraction of fish lipids gives higher values for n-6 fatty acids than ASE method (t(paired)=3.22 t(c)=2.36), while there is no statistically significant difference in the n-3 content levels between the methods (t(paired)=1.31). The UNSFA/SFA ratio obtained by using modified Soxhlet method is also higher than the ratio obtained using ASE method (t(paired)=4.88 t(c)=2.36). Results of Principal Component Analysis (PCA) showed that the highest positive impact to

Statistical model to predict dry sliding wear behaviour of Aluminium-Jute bast ash particulate composite produced by stir-casting

Directory of Open Access Journals (Sweden)

Gambo Anthony VICTOR

2017-06-01

Full Text Available A model to predict the dry sliding wear behaviour of Aluminium-Jute bast ash particulate composites produced by double stir-casting method was developed in terms of weight fraction of jute bast ash (JBA. Experiments were designed on the basis of the Design of Experiments (DOE technique. A 2k factorial, where k is the number of variables, with central composite second-order rotatable design was used to improve the reliability of results and to reduce the size of experimentation without loss of accuracy. The factors considered in this study were sliding velocity, sliding distance, normal load and mass fraction of JBA reinforcement in the matrix. The developed regression model was validated by statistical software MINITAB-R14 and statistical tool such as analysis of variance (ANOVA. It was found that the developed regression model could be effectively used to predict the wear rate at 95% confidence level. The wear rate of cast Al-JBAp composite decreased with an increase in the mass fraction of JBA and increased with an increase of the sliding velocity, sliding distance and normal load acting on the composite specimen.

Analysis of repeated measurement data in the clinical trials

Science.gov (United States)

Singh, Vineeta; Rana, Rakesh Kumar; Singhal, Richa

2013-01-01

Statistics is an integral part of Clinical Trials. Elements of statistics span Clinical Trial design, data monitoring, analyses and reporting. A solid understanding of statistical concepts by clinicians improves the comprehension and the resulting quality of Clinical Trials. In biomedical research it has been seen that researcher frequently use t-test and ANOVA to compare means between the groups of interest irrespective of the nature of the data. In Clinical Trials we record the data on the patients more than two times. In such a situation using the standard ANOVA procedures is not appropriate as it does not consider dependencies between observations within subjects in the analysis. To deal with such types of study data Repeated Measure ANOVA should be used. In this article the application of One-way Repeated Measure ANOVA has been demonstrated by using the software SPSS (Statistical Package for Social Sciences) Version 15.0 on the data collected at four time points 0 day, 15th day, 30th day, and 45th day of multicentre clinical trial conducted on Pandu Roga (~Iron Deficiency Anemia) with an Ayurvedic formulation Dhatrilauha. PMID:23930038

[Comment on] Statistical discrimination

Science.gov (United States)

Chinn, Douglas

In the December 8, 1981, issue of Eos, a news item reported the conclusion of a National Research Council study that sexual discrimination against women with Ph.D.'s exists in the field of geophysics. Basically, the item reported that even when allowances are made for motherhood the percentage of female Ph.D.'s holding high university and corporate positions is significantly lower than the percentage of male Ph.D.'s holding the same types of positions. The sexual discrimination conclusion, based only on these statistics, assumes that there are no basic psychological differences between men and women that might cause different populations in the employment group studied. Therefore, the reasoning goes, after taking into account possible effects from differences related to anatomy, such as women stopping their careers in order to bear and raise children, the statistical distributions of positions held by male and female Ph.D.'s ought to be very similar to one another. Any significant differences between the distributions must be caused primarily by sexual discrimination.

Harmonic statistics

International Nuclear Information System (INIS)

Eliazar, Iddo

2017-01-01

The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their ‘public relations’ for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford’s law, and 1/f noise. - Highlights: • Harmonic statistics are described and reviewed in detail. • Connections to various statistical laws are established. • Connections to perturbation, renormalization and dynamics are established.

Harmonic statistics

Energy Technology Data Exchange (ETDEWEB)

Eliazar, Iddo, E-mail: eliazar@post.tau.ac.il

2017-05-15

The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their ‘public relations’ for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford’s law, and 1/f noise. - Highlights: • Harmonic statistics are described and reviewed in detail. • Connections to various statistical laws are established. • Connections to perturbation, renormalization and dynamics are established.

Effect of cefuroxime and moxifloxacin on Staphylococcus epidermidis adherence to intraocular lenses.

Science.gov (United States)

Karadağ, Serhat; Ozkan, Berna; Karabaş, V Levent; Alintaş, Ozgül; Yumuk, Zeki; Cağlar, Yusuf

2009-12-01

To investigate and compare the effect of cefuroxime and moxifloxacin on adhesion of Staphylococcus epidermidis to intraocular lenses (IOLs). Experimental study. The 3-pieced hydrophobic acrylic lenses were contaminated with S. epidermidis (American Type Culture Collection 35983) solutions containing 108 colony-forming units. IOLs were inoculated into test tubes containing tryptic soy broth after being held in antibiotic solutions for 15 minutes. Sonication and vortex procedures were performed in order to remove all the remaining bacteria. From each tube 10 microL and 100 microL was taken and inoculated into sheep blood agar. The colonies were counted overnight. The statistical analyses were made using one-way ANOVA, Turkey Honestly Significant Differences test (HSD) and independent t tests, and a p value less than 0.05 was considered statistically significant. Overall, the mean numbers of colony-forming units on the lenses that were held in control, cefuroxime, moxifloxacin 0.5 mg/0.1 mL and moxifloxacin 0.1 mg/0.1 mL solutions were 1398 (SE 10.01 x 10(3)), 29.9 (SE 1.16 x 10(3)), 0.23 (SD 0.04 x 10(3)), and 0.41 (SD 0.05 x 10(3)), respectively. The evaluation using one-way ANOVA and Turkey HSD tests revealed significant statistical differences among the groups (p = 0.000). The evaluation using independent t tests revealed significant statistical differences between the 2 moxifloxacin groups (p < 0.05). Our results suggest that moxifloxacin and cefuroxime significantly inhibit bacterial adherence to IOLs. The effect of moxifloxacin on inhibition of bacterial adherence was significantly greater than that of cefuroxime. For this reason moxifloxacin might be considered as a better prophylactic agent.

Statistical mechanics for a class of quantum statistics

International Nuclear Information System (INIS)

Isakov, S.B.

1994-01-01

Generalized statistical distributions for identical particles are introduced for the case where filling a single-particle quantum state by particles depends on filling states of different momenta. The system of one-dimensional bosons with a two-body potential that can be solved by means of the thermodynamic Bethe ansatz is shown to be equivalent thermodynamically to a system of free particles obeying statistical distributions of the above class. The quantum statistics arising in this way are completely determined by the two-particle scattering phases of the corresponding interacting systems. An equation determining the statistical distributions for these statistics is derived

Data-driven inference for the spatial scan statistic.

Science.gov (United States)

Almeida, Alexandre C L; Duarte, Anderson R; Duczmal, Luiz H; Oliveira, Fernando L P; Takahashi, Ricardo H C

2011-08-02

Kulldorff's spatial scan statistic for aggregated area maps searches for clusters of cases without specifying their size (number of areas) or geographic location in advance. Their statistical significance is tested while adjusting for the multiple testing inherent in such a procedure. However, as is shown in this work, this adjustment is not done in an even manner for all possible cluster sizes. A modification is proposed to the usual inference test of the spatial scan statistic, incorporating additional information about the size of the most likely cluster found. A new interpretation of the results of the spatial scan statistic is done, posing a modified inference question: what is the probability that the null hypothesis is rejected for the original observed cases map with a most likely cluster of size k, taking into account only those most likely clusters of size k found under null hypothesis for comparison? This question is especially important when the p-value computed by the usual inference process is near the alpha significance level, regarding the correctness of the decision based in this inference. A practical procedure is provided to make more accurate inferences about the most likely cluster found by the spatial scan statistic.

Medical Statistics – Mathematics or Oracle? Farewell Lecture

Directory of Open Access Journals (Sweden)

Gaus, Wilhelm

2005-06-01

Full Text Available Certainty is rare in medicine. This is a direct consequence of the individuality of each and every human being and the reason why we need medical statistics. However, statistics have their pitfalls, too. Fig. 1 shows that the suicide rate peaks in youth, while in Fig. 2 the rate is highest in midlife and Fig. 3 in old age. Which of these contradictory messages is right? After an introduction to the principles of statistical testing, this lecture examines the probability with which statistical test results are correct. For this purpose the level of significance and the power of the test are compared with the sensitivity and specificity of a diagnostic procedure. The probability of obtaining correct statistical test results is the same as that for the positive and negative correctness of a diagnostic procedure and therefore depends on prevalence. The focus then shifts to the problem of multiple statistical testing. The lecture demonstrates that for each data set of reasonable size at least one test result proves to be significant - even if the data set is produced by a random number generator. It is extremely important that a hypothesis is generated independently from the data used for its testing. These considerations enable us to understand the gradation of "lame excuses, lies and statistics" and the difference between pure truth and the full truth. Finally, two historical oracles are cited.

Testing for significance of phase synchronisation dynamics in the EEG.

Science.gov (United States)

Daly, Ian; Sweeney-Reed, Catherine M; Nasuto, Slawomir J

2013-06-01

A number of tests exist to check for statistical significance of phase synchronisation within the Electroencephalogram (EEG); however, the majority suffer from a lack of generality and applicability. They may also fail to account for temporal dynamics in the phase synchronisation, regarding synchronisation as a constant state instead of a dynamical process. Therefore, a novel test is developed for identifying the statistical significance of phase synchronisation based upon a combination of work characterising temporal dynamics of multivariate time-series and Markov modelling. We show how this method is better able to assess the significance of phase synchronisation than a range of commonly used significance tests. We also show how the method may be applied to identify and classify significantly different phase synchronisation dynamics in both univariate and multivariate datasets.

New scanning technique using Adaptive Statistical lterative Reconstruction (ASIR) significantly reduced the radiation dose of cardiac CT

International Nuclear Information System (INIS)

Tumur, Odgerel; Soon, Kean; Brown, Fraser; Mykytowycz, Marcus

2013-01-01

The aims of our study were to evaluate the effect of application of Adaptive Statistical Iterative Reconstruction (ASIR) algorithm on the radiation dose of coronary computed tomography angiography (CCTA) and its effects on image quality of CCTA and to evaluate the effects of various patient and CT scanning factors on the radiation dose of CCTA. This was a retrospective study that included 347 consecutive patients who underwent CCTA at a tertiary university teaching hospital between 1 July 2009 and 20 September 2011. Analysis was performed comparing patient demographics, scan characteristics, radiation dose and image quality in two groups of patients in whom conventional Filtered Back Projection (FBP) or ASIR was used for image reconstruction. There were 238 patients in the FBP group and 109 patients in the ASIR group. There was no difference between the groups in the use of prospective gating, scan length or tube voltage. In ASIR group, significantly lower tube current was used compared with FBP group, 550mA (450–600) vs. 650mA (500–711.25) (median (interquartile range)), respectively, P<0.001. There was 27% effective radiation dose reduction in the ASIR group compared with FBP group, 4.29mSv (2.84–6.02) vs. 5.84mSv (3.88–8.39) (median (interquartile range)), respectively, P<0.001. Although ASIR was associated with increased image noise compared with FBP (39.93±10.22 vs. 37.63±18.79 (mean ±standard deviation), respectively, P<001), it did not affect the signal intensity, signal-to-noise ratio, contrast-to-noise ratio or the diagnostic quality of CCTA. Application of ASIR reduces the radiation dose of CCTA without affecting the image quality.

Conversion factors and oil statistics

International Nuclear Information System (INIS)

Karbuz, Sohbet

2004-01-01

World oil statistics, in scope and accuracy, are often far from perfect. They can easily lead to misguided conclusions regarding the state of market fundamentals. Without proper attention directed at statistic caveats, the ensuing interpretation of oil market data opens the door to unnecessary volatility, and can distort perception of market fundamentals. Among the numerous caveats associated with the compilation of oil statistics, conversion factors, used to produce aggregated data, play a significant role. Interestingly enough, little attention is paid to conversion factors, i.e. to the relation between different units of measurement for oil. Additionally, the underlying information regarding the choice of a specific factor when trying to produce measurements of aggregated data remains scant. The aim of this paper is to shed some light on the impact of conversion factors for two commonly encountered issues, mass to volume equivalencies (barrels to tonnes) and for broad energy measures encountered in world oil statistics. This paper will seek to demonstrate how inappropriate and misused conversion factors can yield wildly varying results and ultimately distort oil statistics. Examples will show that while discrepancies in commonly used conversion factors may seem trivial, their impact on the assessment of a world oil balance is far from negligible. A unified and harmonised convention for conversion factors is necessary to achieve accurate comparisons and aggregate oil statistics for the benefit of both end-users and policy makers

Statistics with JMP graphs, descriptive statistics and probability

CERN Document Server

Goos, Peter

2015-01-01

Peter Goos, Department of Statistics, University ofLeuven, Faculty of Bio-Science Engineering and University ofAntwerp, Faculty of Applied Economics, BelgiumDavid Meintrup, Department of Mathematics and Statistics,University of Applied Sciences Ingolstadt, Faculty of MechanicalEngineering, GermanyThorough presentation of introductory statistics and probabilitytheory, with numerous examples and applications using JMPDescriptive Statistics and Probability provides anaccessible and thorough overview of the most important descriptivestatistics for nominal, ordinal and quantitative data withpartic

Testing University Rankings Statistically: Why this Perhaps is not such a Good Idea after All. Some Reflections on Statistical Power, Effect Size, Random Sampling and Imaginary Populations

DEFF Research Database (Denmark)

Schneider, Jesper Wiborg

2012-01-01

In this paper we discuss and question the use of statistical significance tests in relation to university rankings as recently suggested. We outline the assumptions behind and interpretations of statistical significance tests and relate this to examples from the recent SCImago Institutions Rankin...

Statistical modeling of an integrated boiler for coal fired thermal power plant.

Science.gov (United States)

Chandrasekharan, Sreepradha; Panda, Rames Chandra; Swaminathan, Bhuvaneswari Natrajan

2017-06-01

The coal fired thermal power plants plays major role in the power production in the world as they are available in abundance. Many of the existing power plants are based on the subcritical technology which can produce power with the efficiency of around 33%. But the newer plants are built on either supercritical or ultra-supercritical technology whose efficiency can be up to 50%. Main objective of the work is to enhance the efficiency of the existing subcritical power plants to compensate for the increasing demand. For achieving the objective, the statistical modeling of the boiler units such as economizer, drum and the superheater are initially carried out. The effectiveness of the developed models is tested using analysis methods like R 2 analysis and ANOVA (Analysis of Variance). The dependability of the process variable (temperature) on different manipulated variables is analyzed in the paper. Validations of the model are provided with their error analysis. Response surface methodology (RSM) supported by DOE (design of experiments) are implemented to optimize the operating parameters. Individual models along with the integrated model are used to study and design the predictive control of the coal-fired thermal power plant.

Uncertainty the soul of modeling, probability & statistics

CERN Document Server

Briggs, William

2016-01-01

This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance". The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models. Its jargon-free approach asserts that standard methods, suc...

Normality of raw data in general linear models: The most widespread myth in statistics

Science.gov (United States)

Kery, Marc; Hatfield, Jeff S.

2003-01-01

In years of statistical consulting for ecologists and wildlife biologists, by far the most common misconception we have come across has been the one about normality in general linear models. These comprise a very large part of the statistical models used in ecology and include t tests, simple and multiple linear regression, polynomial regression, and analysis of variance (ANOVA) and covariance (ANCOVA). There is a widely held belief that the normality assumption pertains to the raw data rather than to the model residuals. We suspect that this error may also occur in countless published studies, whenever the normality assumption is tested prior to analysis. This may lead to the use of nonparametric alternatives (if there are any), when parametric tests would indeed be appropriate, or to use of transformations of raw data, which may introduce hidden assumptions such as multiplicative effects on the natural scale in the case of log-transformed data. Our aim here is to dispel this myth. We very briefly describe relevant theory for two cases of general linear models to show that the residuals need to be normally distributed if tests requiring normality are to be used, such as t and F tests. We then give two examples demonstrating that the distribution of the response variable may be nonnormal, and yet the residuals are well behaved. We do not go into the issue of how to test normality; instead we display the distributions of response variables and residuals graphically.

Error correction and statistical analyses for intra-host comparisons of feline immunodeficiency virus diversity from high-throughput sequencing data.

Science.gov (United States)

Liu, Yang; Chiaromonte, Francesca; Ross, Howard; Malhotra, Raunaq; Elleder, Daniel; Poss, Mary

2015-06-30

Infection with feline immunodeficiency virus (FIV) causes an immunosuppressive disease whose consequences are less severe if cats are co-infected with an attenuated FIV strain (PLV). We use virus diversity measurements, which reflect replication ability and the virus response to various conditions, to test whether diversity of virulent FIV in lymphoid tissues is altered in the presence of PLV. Our data consisted of the 3' half of the FIV genome from three tissues of animals infected with FIV alone, or with FIV and PLV, sequenced by 454 technology. Since rare variants dominate virus populations, we had to carefully distinguish sequence variation from errors due to experimental protocols and sequencing. We considered an exponential-normal convolution model used for background correction of microarray data, and modified it to formulate an error correction approach for minor allele frequencies derived from high-throughput sequencing. Similar to accounting for over-dispersion in counts, this accounts for error-inflated variability in frequencies - and quite effectively reproduces empirically observed distributions. After obtaining error-corrected minor allele frequencies, we applied ANalysis Of VAriance (ANOVA) based on a linear mixed model and found that conserved sites and transition frequencies in FIV genes differ among tissues of dual and single infected cats. Furthermore, analysis of minor allele frequencies at individual FIV genome sites revealed 242 sites significantly affected by infection status (dual vs. single) or infection status by tissue interaction. All together, our results demonstrated a decrease in FIV diversity in bone marrow in the presence of PLV. Importantly, these effects were weakened or undetectable when error correction was performed with other approaches (thresholding of minor allele frequencies; probabilistic clustering of reads). We also queried the data for cytidine deaminase activity on the viral genome, which causes an asymmetric increase

Statistical process control in nursing research.

Science.gov (United States)

Polit, Denise F; Chaboyer, Wendy

2012-02-01

In intervention studies in which randomization to groups is not possible, researchers typically use quasi-experimental designs. Time series designs are strong quasi-experimental designs but are seldom used, perhaps because of technical and analytic hurdles. Statistical process control (SPC) is an alternative analytic approach to testing hypotheses about intervention effects using data collected over time. SPC, like traditional statistical methods, is a tool for understanding variation and involves the construction of control charts that distinguish between normal, random fluctuations (common cause variation), and statistically significant special cause variation that can result from an innovation. The purpose of this article is to provide an overview of SPC and to illustrate its use in a study of a nursing practice improvement intervention. Copyright © 2011 Wiley Periodicals, Inc.

Statistics Anxiety and Business Statistics: The International Student

Science.gov (United States)

Bell, James A.

2008-01-01

Does the international student suffer from statistics anxiety? To investigate this, the Statistics Anxiety Rating Scale (STARS) was administered to sixty-six beginning statistics students, including twelve international students and fifty-four domestic students. Due to the small number of international students, nonparametric methods were used to…

QUALITY OF LIFE OF TOURIST CORRIDORS PARTICIPANTS IN SOUTHERN SONORA, MEXICO/CALIDAD DE VIDA DE LOS PARTICIPANTES DE CORREDORES TURISTICOS EN EL SUR DE SONORA, MEXICO.

OpenAIRE

Irma Guadalupe Esparza Garcia; Altayra Geraldine Ozuna Beltran; Marco Alberto Nunez Ramirez; Rosalva Irma Castro Alvarez; Yesenia Clark Mendivil; Maria Nelida Sanchez Banuelos.

2017-01-01

The aim of the present research is to measure the relationship and difference between the indicators of the quality of life in the participants of the tourist communities of Mexico. Through a Pearson correlation and one-way ANOVA, the empirical evidence shows that the quality of life items within the communities are associated with a positive and significant way and, at the same time, these differ statistically from each other. The statistical analyzes show the emergence of needs, which have ...

Changing world extreme temperature statistics

Science.gov (United States)

Finkel, J. M.; Katz, J. I.

2018-04-01

We use the Global Historical Climatology Network--daily database to calculate a nonparametric statistic that describes the rate at which all-time daily high and low temperature records have been set in nine geographic regions (continents or major portions of continents) during periods mostly from the mid-20th Century to the present. This statistic was defined in our earlier work on temperature records in the 48 contiguous United States. In contrast to this earlier work, we find that in every region except North America all-time high records were set at a rate significantly (at least $3\\sigma$) higher than in the null hypothesis of a stationary climate. Except in Antarctica, all-time low records were set at a rate significantly lower than in the null hypothesis. In Europe, North Africa and North Asia the rate of setting new all-time highs increased suddenly in the 1990's, suggesting a change in regional climate regime; in most other regions there was a steadier increase.

Applying Statistical Mechanics to pixel detectors

International Nuclear Information System (INIS)

Pindo, Massimiliano

2002-01-01

Pixel detectors, being made of a large number of active cells of the same kind, can be considered as significant sets to which Statistical Mechanics variables and methods can be applied. By properly redefining well known statistical parameters in order to let them match the ones that actually characterize pixel detectors, an analysis of the way they work can be performed in a totally new perspective. A deeper understanding of pixel detectors is attained, helping in the evaluation and comparison of their intrinsic characteristics and performance

Introductory statistics for the behavioral sciences

CERN Document Server

Welkowitz, Joan; Cohen, Jacob

1971-01-01

Introductory Statistics for the Behavioral Sciences provides an introduction to statistical concepts and principles. This book emphasizes the robustness of parametric procedures wherein such significant tests as t and F yield accurate results even if such assumptions as equal population variances and normal population distributions are not well met.Organized into three parts encompassing 16 chapters, this book begins with an overview of the rationale upon which much of behavioral science research is based, namely, drawing inferences about a population based on data obtained from a samp

Application of full factorial design to study the tribological properties of AA6061-B4C and AA6061-B4C-MoS2 composites

Directory of Open Access Journals (Sweden)

Monikandan V. V.

2018-03-01

Full Text Available This study statistically analyzes the tribological properties of AA6061-10 wt. % B4C mono composite and AA6061-10 wt.% B4C-7.5 wt. % MoS2 hybrid composite. The tribological behavior of the composites was studied at atmospheric conditions using a pin-on-disk tribo-tester. The tribological experiments were conducted as per the full factorial design (FFD experimental scheme. The ANOVA analysis of the wear rate revealed that the three factors, A (MoS2 particles addition, B (applied load, and D (sliding distance presented the physical and statistical significance on the wear rate. The ANOVA analysis of the friction coefficient revealed that the factors B (applied load and C (sliding speed and interaction AB (interaction of MoS2 particles addition and applied load presented the physical and statistical significance on the friction coefficient. It is observed from the main effects plots of the wear rate and friction coefficient that the increase in the levels of factors B (applied load and D (sliding distance increased the wear rate and friction coefficient. However, the wear rate and friction coefficient decreased with the increase in the level of factor A (MoS2 particles addition.

`Is the Hypothesis Correct’ or `Is it not’? Bayesian Evaluation of One Informative Hypthesis in ANOVA.

NARCIS (Netherlands)

Rossum, Maaike A. van; Schoot, A.G.J. van de; Hoijtink, H.

2011-01-01

Researchers in the behavioral and social sciences often have one informative hypothesis with respect to the state of affairs in the population from which they sampled their data. The question they would like an answer to is ‘‘Is the Hypothesis Correct’’ or ‘‘Is it Not.’’ Classical statistics has

Spreadsheets as tools for statistical computing and statistics education

OpenAIRE

Neuwirth, Erich

2000-01-01

Spreadsheets are an ubiquitous program category, and we will discuss their use in statistics and statistics education on various levels, ranging from very basic examples to extremely powerful methods. Since the spreadsheet paradigm is very familiar to many potential users, using it as the interface to statistical methods can make statistics more easily accessible.

An Exploration of the Perceived Usefulness of the Introductory Statistics Course and Students’ Intentions to Further Engage in Statistics

Directory of Open Access Journals (Sweden)

Rossi Hassad

2018-01-01

Full Text Available Students� attitude, including perceived usefulness, is generally associated with academic success. The related research in statistics education has focused almost exclusively on the role of attitude in explaining and predicting academic learning outcomes, hence there is a paucity of research evidence on how attitude (particularly perceived usefulness impacts students� intentions to use and stay engaged in statistics beyond the introductory course. This study explored the relationship between college students� perception of the usefulness of an introductory statistics course, their beliefs about where statistics will be most useful, and their intentions to take another statistics course. A cross-sectional study of 106 students was conducted. The mean rating for usefulness was 4.7 (out of 7, with no statistically significant differences based on gender and age. Sixty-four percent reported that they would consider taking another statistics course, and this subgroup rated the course as more useful (p = .01. The majority (67% reported that statistics would be most useful for either graduate school or research, whereas 14% indicated their job, and 19% were undecided. The �undecided� students had the lowest mean rating for usefulness of the course (p = .001. Addressing data, in the context of real-world problem-solving and decision-making, could facilitate students to better appreciate the usefulness and practicality of statistics. Qualitative research methods could help to elucidate these findings.

Data-driven inference for the spatial scan statistic

Directory of Open Access Journals (Sweden)

Duczmal Luiz H

2011-08-01

Full Text Available Abstract Background Kulldorff's spatial scan statistic for aggregated area maps searches for clusters of cases without specifying their size (number of areas or geographic location in advance. Their statistical significance is tested while adjusting for the multiple testing inherent in such a procedure. However, as is shown in this work, this adjustment is not done in an even manner for all possible cluster sizes. Results A modification is proposed to the usual inference test of the spatial scan statistic, incorporating additional information about the size of the most likely cluster found. A new interpretation of the results of the spatial scan statistic is done, posing a modified inference question: what is the probability that the null hypothesis is rejected for the original observed cases map with a most likely cluster of size k, taking into account only those most likely clusters of size k found under null hypothesis for comparison? This question is especially important when the p-value computed by the usual inference process is near the alpha significance level, regarding the correctness of the decision based in this inference. Conclusions A practical procedure is provided to make more accurate inferences about the most likely cluster found by the spatial scan statistic.

Register-based statistics statistical methods for administrative data

CERN Document Server

Wallgren, Anders

2014-01-01

This book provides a comprehensive and up to date treatment of  theory and practical implementation in Register-based statistics. It begins by defining the area, before explaining how to structure such systems, as well as detailing alternative approaches. It explains how to create statistical registers, how to implement quality assurance, and the use of IT systems for register-based statistics. Further to this, clear details are given about the practicalities of implementing such statistical methods, such as protection of privacy and the coordination and coherence of such an undertaking. Thi

Cancer Statistics

Science.gov (United States)

... What Is Cancer? Cancer Statistics Cancer Disparities Cancer Statistics Cancer has a major impact on society in ... success of efforts to control and manage cancer. Statistics at a Glance: The Burden of Cancer in ...

Accelerator driven reactors, - the significance of the energy distribution of spallation neutrons on the neutron statistics

Energy Technology Data Exchange (ETDEWEB)

Fhager, V

2000-01-01

In order to make correct predictions of the second moment of statistical nuclear variables, such as the number of fissions and the number of thermalized neutrons, the dependence of the energy distribution of the source particles on their number should be considered. It has been pointed out recently that neglecting this number dependence in accelerator driven systems might result in bad estimates of the second moment, and this paper contains qualitative and quantitative estimates of the size of these efforts. We walk towards the requested results in two steps. First, models of the number dependent energy distributions of the neutrons that are ejected in the spallation reactions are constructed, both by simple assumptions and by extracting energy distributions of spallation neutrons from a high-energy particle transport code. Then, the second moment of nuclear variables in a sub-critical reactor, into which spallation neutrons are injected, is calculated. The results from second moment calculations using number dependent energy distributions for the source neutrons are compared to those where only the average energy distribution is used. Two physical models are employed to simulate the neutron transport in the reactor. One is analytical, treating only slowing down of neutrons by elastic scattering in the core material. For this model, equations are written down and solved for the second moment of thermalized neutrons that include the distribution of energy of the spallation neutrons. The other model utilizes Monte Carlo methods for tracking the source neutrons as they travel inside the reactor material. Fast and thermal fission reactions are considered, as well as neutron capture and elastic scattering, and the second moment of the number of fissions, the number of neutrons that leaked out of the system, etc. are calculated. Both models use a cylindrical core with a homogenous mixture of core material. Our results indicate that the number dependence of the energy

Accelerator driven reactors, - the significance of the energy distribution of spallation neutrons on the neutron statistics

International Nuclear Information System (INIS)

Fhager, V.

2000-01-01

In order to make correct predictions of the second moment of statistical nuclear variables, such as the number of fissions and the number of thermalized neutrons, the dependence of the energy distribution of the source particles on their number should be considered. It has been pointed out recently that neglecting this number dependence in accelerator driven systems might result in bad estimates of the second moment, and this paper contains qualitative and quantitative estimates of the size of these efforts. We walk towards the requested results in two steps. First, models of the number dependent energy distributions of the neutrons that are ejected in the spallation reactions are constructed, both by simple assumptions and by extracting energy distributions of spallation neutrons from a high-energy particle transport code. Then, the second moment of nuclear variables in a sub-critical reactor, into which spallation neutrons are injected, is calculated. The results from second moment calculations using number dependent energy distributions for the source neutrons are compared to those where only the average energy distribution is used. Two physical models are employed to simulate the neutron transport in the reactor. One is analytical, treating only slowing down of neutrons by elastic scattering in the core material. For this model, equations are written down and solved for the second moment of thermalized neutrons that include the distribution of energy of the spallation neutrons. The other model utilizes Monte Carlo methods for tracking the source neutrons as they travel inside the reactor material. Fast and thermal fission reactions are considered, as well as neutron capture and elastic scattering, and the second moment of the number of fissions, the number of neutrons that leaked out of the system, etc. are calculated. Both models use a cylindrical core with a homogenous mixture of core material. Our results indicate that the number dependence of the energy

The Effect of Proprioceptive Neuromuscular Facilitation on Learning Fine Motor Skills: A Preliminary Study

Directory of Open Access Journals (Sweden)

Mohammad Reza Shahabi Kaseb

2016-09-01

Full Text Available Introduction: Preparation of neuromuscular system prior to performing motor skills affects the learning of motor skills. The present study was conducted to investigate the effects of Proprioceptive Neuromuscular Facilitation (PNF on limb coordination and accuracy in dart throwing skill. Methods: Thirty two male students were randomly selected as study sample. Based on the pretest scores, the participants were divided into three groups: experimental (proprioceptive neuromuscular facilitation, first control (without warm-up, and second control (specific warm-up. During the acquisition phase, the participants first performed the preparation training related to their own group, then all groups performed the exercise program of dart throwing consisting of 6 blocks of 9 trials in 4 training sessions. Finally, 20 days following the last exercise session, the subjects took the retention and transfer tests. Results: The results of one-way ANOVA test for coordination variable in acquisition test showed no significant difference between the groups, while there was a statistically significant difference between groups regarding coordination variable in retention and transfer tests. Furthermore, the results of one-way ANOVA for the accuracy variable in acquisition and retention tests showed no statistically significant difference between the three groups, while there was a statistically significant difference between groups for accuracy variable in transfer test. Conclusion: It seems that proprioceptive neuromuscular facilitation, as a preparation method before performance, can enhance the efficacy of training to better learn the coordination pattern of fine motor skills.

CD8+ T cell infiltration in breast and colon cancer: A histologic and statistical analysis.

Directory of Open Access Journals (Sweden)

James Ziai

Full Text Available The prevalence of cytotoxic tumor infiltrating lymphocytes (TILs has demonstrated prognostic value in multiple tumor types. In particular, CD8 counts (in combination with CD3 and CD45RO have been shown to be superior to traditional UICC staging in colon cancer patients and higher total CD8 counts have been associated with better survival in breast cancer patients. However, immune infiltrate heterogeneity can lead to potentially significant misrepresentations of marker prevalence in routine histologic sections. We examined step sections of breast and colorectal cancer samples for CD8+ T cell prevalence by standard chromogenic immunohistochemistry to determine marker variability and inform practice of T cell biomarker assessment in formalin-fixed, paraffin-embedded (FFPE tissue samples. Stained sections were digitally imaged and CD8+ lymphocytes within defined regions of interest (ROI including the tumor and surrounding stroma were enumerated. Statistical analyses of CD8+ cell count variability using a linear model/ANOVA framework between patients as well as between levels within a patient sample were performed. Our results show that CD8+ T-cell distribution is highly homogeneous within a standard tissue sample in both colorectal and breast carcinomas. As such, cytotoxic T cell prevalence by immunohistochemistry on a single level or even from a subsample of biopsy fragments taken from that level can be considered representative of cytotoxic T cell infiltration for the entire tumor section within the block. These findings support the technical validity of biomarker strategies relying on CD8 immunohistochemistry.

Software Used to Generate Cancer Statistics - SEER Cancer Statistics

Science.gov (United States)

Videos that highlight topics and trends in cancer statistics and definitions of statistical terms. Also software tools for analyzing and reporting cancer statistics, which are used to compile SEER's annual reports.

Mental and Reproductive Health Correlates of Academic Performance among Debre Berhan University Female Students, Ethiopia: The Case of Premenstrual Dysphoric Disorder.

Science.gov (United States)

Alemu, Sisay Mulugeta; Habtewold, Tesfa Dejenie; Haile, Yohannes Gebreegziabhere

2017-01-01

Globally 3 to 8% of reproductive age women are suffering from premenstrual dysphoric disorder (PMDD). Several mental and reproductive health-related factors cause low academic achievement during university education. However, limited data exist in Ethiopia. The aim of the study was to investigate mental and reproductive health correlates of academic performance. Institution based cross-sectional study was conducted with 667 Debre Berhan University female students from April to June 2015. Academic performance was the outcome variable. Mental and reproductive health characteristics were explanatory variables. Two-way analysis of variance (ANOVA) test of association was applied to examine group difference in academic performance. Among 529 students who participated, 49.3% reported mild premenstrual syndrome (PMS), 36.9% reported moderate/severe PMS, and 13.8% fulfilled PMDD diagnostic criteria. The ANOVA test of association revealed that there was no significant difference in academic performance between students with different level of PMS experience ( F -statistic = 0.08, p value = 0.93). Nevertheless, there was a significant difference in academic performance between students with different length of menses ( F -statistic = 5.15, p value = 0.006). There was no significant association between PMS experience and academic performance, but on the other hand, the length of menses significantly associated with academic performance.

Comparison of four software packages for CT lung volumetry in healthy individuals

Energy Technology Data Exchange (ETDEWEB)

Nemec, Stefan F. [Harvard Medical School, Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA (United States); Medical University of Vienna, Department of Biomedical Imaging and Image-guided Therapy, Vienna (Austria); Molinari, Francesco [Centre Hospitalier Regional Universitaire de Lille, Department of Radiology, Lille (France); Dufresne, Valerie [CHU de Charleroi - Hopital Vesale, Pneumologie, Montigny-le-Tilleul (Belgium); Gosset, Natacha [CHU Tivoli, Service d' Imagerie Medicale, La Louviere (Belgium); Silva, Mario; Bankier, Alexander A. [Harvard Medical School, Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA (United States)

2015-06-01

To compare CT lung volumetry (CTLV) measurements provided by different software packages, and to provide normative data for lung densitometric measurements in healthy individuals. This retrospective study included 51 chest CTs of 17 volunteers (eight men and nine women; mean age, 30 ± 6 years), who underwent spirometrically monitored CT at total lung capacity (TLC), functional residual capacity (FRC), and mean inspiratory capacity (MIC). Volumetric differences assessed by four commercial software packages were compared with analysis of variance (ANOVA) for repeated measurements and benchmarked against the threshold for acceptable variability between spirometric measurements. Mean lung density (MLD) and parenchymal heterogeneity (MLD-SD) were also compared with ANOVA. Volumetric differences ranged from 12 to 213 ml (0.20 % to 6.45 %). Although 16/18 comparisons (among four software packages at TLC, MIC, and FRC) were statistically significant (P < 0.001 to P = 0.004), only 3/18 comparisons, one at MIC and two at FRC, exceeded the spirometry variability threshold. MLD and MLD-SD significantly increased with decreasing volumes, and were significantly larger in lower compared to upper lobes (P < 0.001). Lung volumetric differences provided by different software packages are small. These differences should not be interpreted based on statistical significance alone, but together with absolute volumetric differences. (orig.)

Understanding Statistics and Statistics Education: A Chinese Perspective

Science.gov (United States)

Shi, Ning-Zhong; He, Xuming; Tao, Jian

2009-01-01

In recent years, statistics education in China has made great strides. However, there still exists a fairly large gap with the advanced levels of statistics education in more developed countries. In this paper, we identify some existing problems in statistics education in Chinese schools and make some proposals as to how they may be overcome. We…

Mathematical statistics

CERN Document Server

Pestman, Wiebe R

2009-01-01

This textbook provides a broad and solid introduction to mathematical statistics, including the classical subjects hypothesis testing, normal regression analysis, and normal analysis of variance. In addition, non-parametric statistics and vectorial statistics are considered, as well as applications of stochastic analysis in modern statistics, e.g., Kolmogorov-Smirnov testing, smoothing techniques, robustness and density estimation. For students with some elementary mathematical background. With many exercises. Prerequisites from measure theory and linear algebra are presented.

Evaluating statistical and clinical significance of intervention effects in single-case experimental designs: An SPSS method to analyze univariate data

NARCIS (Netherlands)

Maric, M.; de Haan, M.; Hogendoorn, S.M.; Wolters, L.H.; Huizenga, H.M.

2015-01-01

Single-case experimental designs are useful methods in clinical research practice to investigate individual client progress. Their proliferation might have been hampered by methodological challenges such as the difficulty applying existing statistical procedures. In this article, we describe a

Evaluating statistical and clinical significance of intervention effects in single-case experimental designs: an SPSS method to analyze univariate data

NARCIS (Netherlands)

Maric, Marija; de Haan, Else; Hogendoorn, Sanne M.; Wolters, Lidewij H.; Huizenga, Hilde M.

2015-01-01

Single-case experimental designs are useful methods in clinical research practice to investigate individual client progress. Their proliferation might have been hampered by methodological challenges such as the difficulty applying existing statistical procedures. In this article, we describe a

Statistical inference and visualization in scale-space for spatially dependent images

KAUST Repository

Vaughan, Amy

2012-03-01

SiZer (SIgnificant ZERo crossing of the derivatives) is a graphical scale-space visualization tool that allows for statistical inferences. In this paper we develop a spatial SiZer for finding significant features and conducting goodness-of-fit tests for spatially dependent images. The spatial SiZer utilizes a family of kernel estimates of the image and provides not only exploratory data analysis but also statistical inference with spatial correlation taken into account. It is also capable of comparing the observed image with a specific null model being tested by adjusting the statistical inference using an assumed covariance structure. Pixel locations having statistically significant differences between the image and a given null model are highlighted by arrows. The spatial SiZer is compared with the existing independent SiZer via the analysis of simulated data with and without signal on both planar and spherical domains. We apply the spatial SiZer method to the decadal temperature change over some regions of the Earth. © 2011 The Korean Statistical Society.

The Role of Statistics in Business and Industry

CERN Document Server

Hahn, Gerald J

2011-01-01

An insightful guide to the use of statistics for solving key problems in modern-day business and industry This book has been awarded the Technometrics Ziegel Prize for the best book reviewed by the journal in 2010. Technometrics is a journal of statistics for the physical, chemical and engineering sciences, published jointly by the American Society for Quality and the American Statistical Association. Criteria for the award include that the book brings together in one volume a body of material previously only available in scattered research articles and having the potential to significantly im

WASP (Write a Scientific Paper) using Excel 9: Analysis of variance.

Science.gov (United States)

Grech, Victor

2018-06-01

Analysis of variance (ANOVA) may be required by researchers as an inferential statistical test when more than two means require comparison. This paper explains how to perform ANOVA in Microsoft Excel. Copyright © 2018 Elsevier B.V. All rights reserved.

Sampling, Probability Models and Statistical Reasoning Statistical

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 5. Sampling, Probability Models and Statistical Reasoning Statistical Inference. Mohan Delampady V R Padmawar. General Article Volume 1 Issue 5 May 1996 pp 49-58 ...

Statistical Symbolic Execution with Informed Sampling

Science.gov (United States)

Filieri, Antonio; Pasareanu, Corina S.; Visser, Willem; Geldenhuys, Jaco

2014-01-01

Symbolic execution techniques have been proposed recently for the probabilistic analysis of programs. These techniques seek to quantify the likelihood of reaching program events of interest, e.g., assert violations. They have many promising applications but have scalability issues due to high computational demand. To address this challenge, we propose a statistical symbolic execution technique that performs Monte Carlo sampling of the symbolic program paths and uses the obtained information for Bayesian estimation and hypothesis testing with respect to the probability of reaching the target events. To speed up the convergence of the statistical analysis, we propose Informed Sampling, an iterative symbolic execution that first explores the paths that have high statistical significance, prunes them from the state space and guides the execution towards less likely paths. The technique combines Bayesian estimation with a partial exact analysis for the pruned paths leading to provably improved convergence of the statistical analysis. We have implemented statistical symbolic execution with in- formed sampling in the Symbolic PathFinder tool. We show experimentally that the informed sampling obtains more precise results and converges faster than a purely statistical analysis and may also be more efficient than an exact symbolic analysis. When the latter does not terminate symbolic execution with informed sampling can give meaningful results under the same time and memory limits.

Statistical shape analysis with applications in R

CERN Document Server

Dryden, Ian L

2016-01-01

A thoroughly revised and updated edition of this introduction to modern statistical methods for shape analysis Shape analysis is an important tool in the many disciplines where objects are compared using geometrical features. Examples include comparing brain shape in schizophrenia; investigating protein molecules in bioinformatics; and describing growth of organisms in biology. This book is a significant update of the highly-regarded `Statistical Shape Analysis’ by the same authors. The new edition lays the foundations of landmark shape analysis, including geometrical concepts and statistical techniques, and extends to include analysis of curves, surfaces, images and other types of object data. Key definitions and concepts are discussed throughout, and the relative merits of different approaches are presented. The authors have included substantial new material on recent statistical developments and offer numerous examples throughout the text. Concepts are introduced in an accessible manner, while reta...

Static magnetic field therapy for symptomatic diabetic neuropathy: a randomized, double-blind, placebo-controlled trial.

Science.gov (United States)

Weintraub, Michael I; Wolfe, Gil I; Barohn, Richard A; Cole, Steven P; Parry, Gareth J; Hayat, Ghazala; Cohen, Jeffrey A; Page, Jeffrey C; Bromberg, Mark B; Schwartz, Sherwyn L

2003-05-01

To determine if constant wearing of multipolar, static magnetic (450G) shoe insoles can reduce neuropathic pain and quality of life (QOL) scores in symptomatic diabetic peripheral neuropathy (DPN). Randomized, placebo-control, parallel study. Forty-eight centers in 27 states. Three hundred seventy-five subjects with DPN stage II or III were randomly assigned to wear constantly magnetized insoles for 4 months; the placebo group wore similar, unmagnetized device. Nerve conduction and/or quantified sensory testing were performed serially. Daily visual analog scale scores for numbness or tingling and burning and QOL issues were tabulated over 4 months. Secondary measures included nerve conduction changes, role of placebo, and safety issues. Analysis of variance (ANOVA), analysis of covariance (ANCOVA), and chi-square analysis were performed. There were statistically significant reductions during the third and fourth months in burning (mean change for magnet treatment, -12%; for sham, -3%; P<.05, ANCOVA), numbness and tingling (magnet, -10%; sham, +1%; P<.05, ANCOVA), and exercise-induced foot pain (magnet, -12%; sham, -4%; P<.05, ANCOVA). For a subset of patients with baseline severe pain, statistically significant reductions occurred from baseline through the fourth month in numbness and tingling (magnet, -32%; sham, -14%; P<.01, ANOVA) and foot pain (magnet, -41%; sham, -21%; P<.01, ANOVA). Static magnetic fields can penetrate up to 20mm and appear to target the ectopic firing nociceptors in the epidermis and dermis. Analgesic benefits were achieved over time.

Statistics

International Nuclear Information System (INIS)

2005-01-01

For the years 2004 and 2005 the figures shown in the tables of Energy Review are partly preliminary. The annual statistics published in Energy Review are presented in more detail in a publication called Energy Statistics that comes out yearly. Energy Statistics also includes historical time-series over a longer period of time (see e.g. Energy Statistics, Statistics Finland, Helsinki 2004.) The applied energy units and conversion coefficients are shown in the back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO 2 -emissions, Supplies and total consumption of electricity GWh, Energy imports by country of origin in January-June 2003, Energy exports by recipient country in January-June 2003, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes, precautionary stock fees and oil pollution fees

Frog Statistics

Science.gov (United States)

Whole Frog Project and Virtual Frog Dissection Statistics wwwstats output for January 1 through duplicate or extraneous accesses. For example, in these statistics, while a POST requesting an image is as well. Note that this under-represents the bytes requested. Starting date for following statistics

Teaching biology through statistics: application of statistical methods in genetics and zoology courses.

Science.gov (United States)

Colon-Berlingeri, Migdalisel; Burrowes, Patricia A

2011-01-01

Incorporation of mathematics into biology curricula is critical to underscore for undergraduate students the relevance of mathematics to most fields of biology and the usefulness of developing quantitative process skills demanded in modern biology. At our institution, we have made significant changes to better integrate mathematics into the undergraduate biology curriculum. The curricular revision included changes in the suggested course sequence, addition of statistics and precalculus as prerequisites to core science courses, and incorporating interdisciplinary (math-biology) learning activities in genetics and zoology courses. In this article, we describe the activities developed for these two courses and the assessment tools used to measure the learning that took place with respect to biology and statistics. We distinguished the effectiveness of these learning opportunities in helping students improve their understanding of the math and statistical concepts addressed and, more importantly, their ability to apply them to solve a biological problem. We also identified areas that need emphasis in both biology and mathematics courses. In light of our observations, we recommend best practices that biology and mathematics academic departments can implement to train undergraduates for the demands of modern biology.

Effects of quantum coherence on work statistics

Science.gov (United States)

Xu, Bao-Ming; Zou, Jian; Guo, Li-Sha; Kong, Xiang-Mu

2018-05-01

In the conventional two-point measurement scheme of quantum thermodynamics, quantum coherence is destroyed by the first measurement. But as we know the coherence really plays an important role in the quantum thermodynamics process, and how to describe the work statistics for a quantum coherent process is still an open question. In this paper, we use the full counting statistics method to investigate the effects of quantum coherence on work statistics. First, we give a general discussion and show that for a quantum coherent process, work statistics is very different from that of the two-point measurement scheme, specifically the average work is increased or decreased and the work fluctuation can be decreased by quantum coherence, which strongly depends on the relative phase, the energy level structure, and the external protocol. Then, we concretely consider a quenched one-dimensional transverse Ising model and show that quantum coherence has a more significant influence on work statistics in the ferromagnetism regime compared with that in the paramagnetism regime, so that due to the presence of quantum coherence the work statistics can exhibit the critical phenomenon even at high temperature.

Statistical learning and selective inference.

Science.gov (United States)

Taylor, Jonathan; Tibshirani, Robert J

2015-06-23

We describe the problem of "selective inference." This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have "cherry-picked"--searched for the strongest associations--means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis.

Effects of cutting disturbance in Schoenoplectus californicus (C.A. Mey. Soják on the benthic macroinvertebrates - doi: 10.4025/actascibiolsci.v33i1.6383 Effects of cutting disturbance in Schoenoplectus californicus (C.A. Mey. Soják on the benthic macroinvertebrates - doi: 10.4025/actascibiolsci.v33i1.6383

Directory of Open Access Journals (Sweden)

Norma Luiza Würdig

2011-02-01

Full Text Available Lagoons are considered protected areas because these systems play a key ecological role. However, the extraction of macrophyte Schoenoplectus californicus is held for manufacture of handcrafts, being an alternative income for riverbank communities. This study evaluated the impact of S. californicus experimental cutting on benthic macroinvertebrates trough a field experiment. Macroinvertebrates were sampled at 1, 12, 26 and 60 days after the macrophyte cutting in demarked plots (1 m², as well at control plots. The families number was not statistically different (ANOVA, p > 0.05, but the total density of invertebrates, and the density of Ceratopogonidae were significant (ANOVA, p S. californicus, in this area, as the intensity of the cut held, did not affect considerably the aquatic macroinvertebrates. The results suggest that the small-scale extractivism in these regions carries little effect because the fauna of adjacent areas probably can quickly colonize the disturbed areas.Lagoons are considered protected areas because these systems play a key ecological role. However, the extraction of macrophyte Schoenoplectus californicus is held for manufacture of handcrafts, being an alternative income for riverbank communities. This study evaluated the impact of S. californicus experimental cutting on benthic macroinvertebrates trough a field experiment. Macroinvertebrates were sampled at 1, 12, 26 and 60 days after the macrophyte cutting in demarked plots (1 m², as well at control plots. The families number was not statistically different (ANOVA, p > 0.05, but the total density of invertebrates, and the density of Ceratopogonidae were significant (ANOVA, p S. californicus, in this area, as the intensity of the cut held, did not affect considerably the aquatic macroinvertebrates. The results suggest that the small-scale extractivism in these regions carries little effect because the fauna of adjacent areas probably can quickly colonize the disturbed

A study on the compatibility between one-bottle dentin adhesives and composite resins using micro-shear bond strength.

Science.gov (United States)

Song, Minju; Shin, Yooseok; Park, Jeong-Won; Roh, Byoung-Duck

2015-02-01

This study was performed to determine whether the combined use of one-bottle self-etch adhesives and composite resins from same manufacturers have better bond strengths than combinations of adhesive and resins from different manufacturers. 25 experimental micro-shear bond test groups were made from combinations of five dentin adhesives and five composite resins with extracted human molars stored in saline for 24 hr. Testing was performed using the wire-loop method and a universal testing machine. Bond strength data was statistically analyzed using two way analysis of variance (ANOVA) and Tukey's post hoc test. Two way ANOVA revealed significant differences for the factors of dentin adhesives and composite resins, and significant interaction effect (p composite resin (p composite resin than other manufacturer's composite resin. Not all combinations of adhesive and composite resin by same manufacturers failed to show significantly higher bond strengths than mixed manufacturer combinations.

Statistical reporting inconsistencies in experimental philosophy.

Science.gov (United States)

Colombo, Matteo; Duev, Georgi; Nuijten, Michèle B; Sprenger, Jan

2018-01-01

Experimental philosophy (x-phi) is a young field of research in the intersection of philosophy and psychology. It aims to make progress on philosophical questions by using experimental methods traditionally associated with the psychological and behavioral sciences, such as null hypothesis significance testing (NHST). Motivated by recent discussions about a methodological crisis in the behavioral sciences, questions have been raised about the methodological standards of x-phi. Here, we focus on one aspect of this question, namely the rate of inconsistencies in statistical reporting. Previous research has examined the extent to which published articles in psychology and other behavioral sciences present statistical inconsistencies in reporting the results of NHST. In this study, we used the R package statcheck to detect statistical inconsistencies in x-phi, and compared rates of inconsistencies in psychology and philosophy. We found that rates of inconsistencies in x-phi are lower than in the psychological and behavioral sciences. From the point of view of statistical reporting consistency, x-phi seems to do no worse, and perhaps even better, than psychological science.

Statistical reporting inconsistencies in experimental philosophy

Science.gov (United States)

Colombo, Matteo; Duev, Georgi; Nuijten, Michèle B.; Sprenger, Jan

2018-01-01

Experimental philosophy (x-phi) is a young field of research in the intersection of philosophy and psychology. It aims to make progress on philosophical questions by using experimental methods traditionally associated with the psychological and behavioral sciences, such as null hypothesis significance testing (NHST). Motivated by recent discussions about a methodological crisis in the behavioral sciences, questions have been raised about the methodological standards of x-phi. Here, we focus on one aspect of this question, namely the rate of inconsistencies in statistical reporting. Previous research has examined the extent to which published articles in psychology and other behavioral sciences present statistical inconsistencies in reporting the results of NHST. In this study, we used the R package statcheck to detect statistical inconsistencies in x-phi, and compared rates of inconsistencies in psychology and philosophy. We found that rates of inconsistencies in x-phi are lower than in the psychological and behavioral sciences. From the point of view of statistical reporting consistency, x-phi seems to do no worse, and perhaps even better, than psychological science. PMID:29649220

Statistical Analysis of Big Data on Pharmacogenomics

Science.gov (United States)

Fan, Jianqing; Liu, Han

2013-01-01

This paper discusses statistical methods for estimating complex correlation structure from large pharmacogenomic datasets. We selectively review several prominent statistical methods for estimating large covariance matrix for understanding correlation structure, inverse covariance matrix for network modeling, large-scale simultaneous tests for selecting significantly differently expressed genes and proteins and genetic markers for complex diseases, and high dimensional variable selection for identifying important molecules for understanding molecule mechanisms in pharmacogenomics. Their applications to gene network estimation and biomarker selection are used to illustrate the methodological power. Several new challenges of Big data analysis, including complex data distribution, missing data, measurement error, spurious correlation, endogeneity, and the need for robust statistical methods, are also discussed. PMID:23602905

Analysis of statistical misconception in terms of statistical reasoning

Science.gov (United States)

Maryati, I.; Priatna, N.

2018-05-01

Reasoning skill is needed for everyone to face globalization era, because every person have to be able to manage and use information from all over the world which can be obtained easily. Statistical reasoning skill is the ability to collect, group, process, interpret, and draw conclusion of information. Developing this skill can be done through various levels of education. However, the skill is low because many people assume that statistics is just the ability to count and using formulas and so do students. Students still have negative attitude toward course which is related to research. The purpose of this research is analyzing students’ misconception in descriptive statistic course toward the statistical reasoning skill. The observation was done by analyzing the misconception test result and statistical reasoning skill test; observing the students’ misconception effect toward statistical reasoning skill. The sample of this research was 32 students of math education department who had taken descriptive statistic course. The mean value of misconception test was 49,7 and standard deviation was 10,6 whereas the mean value of statistical reasoning skill test was 51,8 and standard deviation was 8,5. If the minimal value is 65 to state the standard achievement of a course competence, students’ mean value is lower than the standard competence. The result of students’ misconception study emphasized on which sub discussion that should be considered. Based on the assessment result, it was found that students’ misconception happen on this: 1) writing mathematical sentence and symbol well, 2) understanding basic definitions, 3) determining concept that will be used in solving problem. In statistical reasoning skill, the assessment was done to measure reasoning from: 1) data, 2) representation, 3) statistic format, 4) probability, 5) sample, and 6) association.

Statistical Inference at Work: Statistical Process Control as an Example

Science.gov (United States)

Bakker, Arthur; Kent, Phillip; Derry, Jan; Noss, Richard; Hoyles, Celia

2008-01-01

To characterise statistical inference in the workplace this paper compares a prototypical type of statistical inference at work, statistical process control (SPC), with a type of statistical inference that is better known in educational settings, hypothesis testing. Although there are some similarities between the reasoning structure involved in…

What can we learn from noise? - Mesoscopic nonequilibrium statistical physics.

Science.gov (United States)

Kobayashi, Kensuke

2016-01-01

Mesoscopic systems - small electric circuits working in quantum regime - offer us a unique experimental stage to explorer quantum transport in a tunable and precise way. The purpose of this Review is to show how they can contribute to statistical physics. We introduce the significance of fluctuation, or equivalently noise, as noise measurement enables us to address the fundamental aspects of a physical system. The significance of the fluctuation theorem (FT) in statistical physics is noted. We explain what information can be deduced from the current noise measurement in mesoscopic systems. As an important application of the noise measurement to statistical physics, we describe our experimental work on the current and current noise in an electron interferometer, which is the first experimental test of FT in quantum regime. Our attempt will shed new light in the research field of mesoscopic quantum statistical physics.

A Statistical Primer: Understanding Descriptive and Inferential Statistics

OpenAIRE

Gillian Byrne

2007-01-01

As libraries and librarians move more towards evidence‐based decision making, the data being generated in libraries is growing. Understanding the basics of statistical analysis is crucial for evidence‐based practice (EBP), in order to correctly design and analyze researchas well as to evaluate the research of others. This article covers the fundamentals of descriptive and inferential statistics, from hypothesis construction to sampling to common statistical techniques including chi‐square, co...

Solution of the statistical bootstrap with Bose statistics

International Nuclear Information System (INIS)

Engels, J.; Fabricius, K.; Schilling, K.

1977-01-01

A brief and transparent way to introduce Bose statistics into the statistical bootstrap of Hagedorn and Frautschi is presented. The resulting bootstrap equation is solved by a cluster expansion for the grand canonical partition function. The shift of the ultimate temperature due to Bose statistics is determined through an iteration process. We discuss two-particle spectra of the decaying fireball (with given mass) as obtained from its grand microcanonical level density

Descriptive and inferential statistical methods used in burns research.

Science.gov (United States)

Al-Benna, Sammy; Al-Ajam, Yazan; Way, Benjamin; Steinstraesser, Lars

2010-05-01

Burns research articles utilise a variety of descriptive and inferential methods to present and analyse data. The aim of this study was to determine the descriptive methods (e.g. mean, median, SD, range, etc.) and survey the use of inferential methods (statistical tests) used in articles in the journal Burns. This study defined its population as all original articles published in the journal Burns in 2007. Letters to the editor, brief reports, reviews, and case reports were excluded. Study characteristics, use of descriptive statistics and the number and types of statistical methods employed were evaluated. Of the 51 articles analysed, 11(22%) were randomised controlled trials, 18(35%) were cohort studies, 11(22%) were case control studies and 11(22%) were case series. The study design and objectives were defined in all articles. All articles made use of continuous and descriptive data. Inferential statistics were used in 49(96%) articles. Data dispersion was calculated by standard deviation in 30(59%). Standard error of the mean was quoted in 19(37%). The statistical software product was named in 33(65%). Of the 49 articles that used inferential statistics, the tests were named in 47(96%). The 6 most common tests used (Student's t-test (53%), analysis of variance/co-variance (33%), chi(2) test (27%), Wilcoxon & Mann-Whitney tests (22%), Fisher's exact test (12%)) accounted for the majority (72%) of statistical methods employed. A specified significance level was named in 43(88%) and the exact significance levels were reported in 28(57%). Descriptive analysis and basic statistical techniques account for most of the statistical tests reported. This information should prove useful in deciding which tests should be emphasised in educating burn care professionals. These results highlight the need for burn care professionals to have a sound understanding of basic statistics, which is crucial in interpreting and reporting data. Advice should be sought from professionals

Statistical methods

CERN Document Server

Szulc, Stefan

1965-01-01

Statistical Methods provides a discussion of the principles of the organization and technique of research, with emphasis on its application to the problems in social statistics. This book discusses branch statistics, which aims to develop practical ways of collecting and processing numerical data and to adapt general statistical methods to the objectives in a given field.Organized into five parts encompassing 22 chapters, this book begins with an overview of how to organize the collection of such information on individual units, primarily as accomplished by government agencies. This text then

Statistical optics

CERN Document Server

Goodman, Joseph W

2015-01-01

This book discusses statistical methods that are useful for treating problems in modern optics, and the application of these methods to solving a variety of such problems This book covers a variety of statistical problems in optics, including both theory and applications.  The text covers the necessary background in statistics, statistical properties of light waves of various types, the theory of partial coherence and its applications, imaging with partially coherent light, atmospheric degradations of images, and noise limitations in the detection of light. New topics have been introduced i

The Impact of Silent and Freeze-Frame Viewing Techniques of Video Materials on the Intermediate EFL Learners’ Listening Comprehension

Directory of Open Access Journals (Sweden)

Sara Shahani

2015-05-01

Full Text Available The use of modern technologies has been widely prevalent among language learners, and video, in particular, as a valuable learning tool provides learners with comprehensible input. The present study investigated the effect of silent and freeze-frame viewing techniques of video materials on the intermediate English as a foreign language (EFL learners’ listening comprehension. To this end, 45 intermediate EFL learners participated in this quasi-experimental study. The results of one-way ANOVA revealed that there was a statistically significant difference between the experimental groups (using two types of viewing techniques and the control group. While the difference between the two experimental groups was not statistically significant, the experimental groups outperformed the control group significantly.

All of statistics a concise course in statistical inference

CERN Document Server

Wasserman, Larry

2004-01-01

This book is for people who want to learn probability and statistics quickly It brings together many of the main ideas in modern statistics in one place The book is suitable for students and researchers in statistics, computer science, data mining and machine learning This book covers a much wider range of topics than a typical introductory text on mathematical statistics It includes modern topics like nonparametric curve estimation, bootstrapping and classification, topics that are usually relegated to follow-up courses The reader is assumed to know calculus and a little linear algebra No previous knowledge of probability and statistics is required The text can be used at the advanced undergraduate and graduate level Larry Wasserman is Professor of Statistics at Carnegie Mellon University He is also a member of the Center for Automated Learning and Discovery in the School of Computer Science His research areas include nonparametric inference, asymptotic theory, causality, and applications to astrophysics, bi...

Significance of acceleration period in a dynamic strength testing study.

Science.gov (United States)

Chen, W L; Su, F C; Chou, Y L

1994-06-01

The acceleration period that occurs during isokinetic tests may provide valuable information regarding neuromuscular readiness to produce maximal contraction. The purpose of this study was to collect the normative data of acceleration time during isokinetic knee testing, to calculate the acceleration work (Wacc), and to determine the errors (ERexp, ERwork, ERpower) due to ignoring Wacc during explosiveness, total work, and average power measurements. Seven male and 13 female subjects attended the test by using the Cybex 325 system and electronic stroboscope machine for 10 testing speeds (30-300 degrees/sec). A three-way ANOVA was used to assess gender, direction, and speed factors on acceleration time, Wacc, and errors. The results indicated that acceleration time was significantly affected by speed and direction; Wacc and ERexp by speed, direction, and gender; and ERwork and ERpower by speed and gender. The errors appeared to increase when testing the female subjects, during the knee flexion test, or when speed increased. To increase validity in clinical testing, it is important to consider the acceleration phase effect, especially in higher velocity isokinetic testing or for weaker muscle groups.

Computed statistics at streamgages, and methods for estimating low-flow frequency statistics and development of regional regression equations for estimating low-flow frequency statistics at ungaged locations in Missouri

Science.gov (United States)

Southard, Rodney E.

2013-01-01

located in Region 1, 120 were located in Region 2, and 10 were located in Region 3. Streamgages located outside of Missouri were selected to extend the range of data used for the independent variables in the regression analyses. Streamgages included in the regression analyses had 10 or more years of record and were considered to be affected minimally by anthropogenic activities or trends. Regional regression analyses identified three characteristics as statistically significant for the development of regional equations. For Region 1, drainage area, longest flow path, and streamflow-variability index were statistically significant. The range in the standard error of estimate for Region 1 is 79.6 to 94.2 percent. For Region 2, drainage area and streamflow variability index were statistically significant, and the range in the standard error of estimate is 48.2 to 72.1 percent. For Region 3, drainage area and streamflow-variability index also were statistically significant with a range in the standard error of estimate of 48.1 to 96.2 percent. Limitations on the use of estimating low-flow frequency statistics at ungaged locations are dependent on the method used. The first method outlined for use in Missouri, power curve equations, were developed to estimate the selected statistics for ungaged locations on 28 selected streams with multiple streamgages located on the same stream. A second method uses a drainage-area ratio to compute statistics at an ungaged location using data from a single streamgage on the same stream with 10 or more years of record. Ungaged locations on these streams may use the ratio of the drainage area at an ungaged location to the drainage area at a streamgage location to scale the selected statistic value from the streamgage location to the ungaged location. This method can be used if the drainage area of the ungaged location is within 40 to 150 percent of the streamgage drainage area. The third method is the use of the regional regression equations

MQSA National Statistics

Science.gov (United States)

... Standards Act and Program MQSA Insights MQSA National Statistics Share Tweet Linkedin Pin it More sharing options ... but should level off with time. Archived Scorecard Statistics 2018 Scorecard Statistics 2017 Scorecard Statistics 2016 Scorecard ...

ANOVA parameters influence in LCF experimental data and simulation results

Directory of Open Access Journals (Sweden)

Vercelli A.

2010-06-01

structural FEM simulations have been used to assess specimens life by means of several damage models implemented in two dedicated softwares. One of them is commercial life estimation software and the second one has been developed by the present research group. The life estimations results obtained from the two softwares and from the damage models have been compared with experimental duration in different test conditions. A statistical analysis of life estimation results allowed evaluating the effectiveness of the procedure.

Inverse Statistics in the Foreign Exchange Market

OpenAIRE

Jensen, M. H.; Johansen, A.; Petroni, F.; Simonsen, I.

2004-01-01

We investigate intra-day foreign exchange (FX) time series using the inverse statistic analysis developed in [1,2]. Specifically, we study the time-averaged distributions of waiting times needed to obtain a certain increase (decrease) $\\rho$ in the price of an investment. The analysis is performed for the Deutsch mark (DM) against the $US for the full year of 1998, but similar results are obtained for the Japanese Yen against the $US. With high statistical significance, the presence of "reson...

Generalized quantum statistics

International Nuclear Information System (INIS)

Chou, C.

1992-01-01

In the paper, a non-anyonic generalization of quantum statistics is presented, in which Fermi-Dirac statistics (FDS) and Bose-Einstein statistics (BES) appear as two special cases. The new quantum statistics, which is characterized by the dimension of its single particle Fock space, contains three consistent parts, namely the generalized bilinear quantization, the generalized quantum mechanical description and the corresponding statistical mechanics

Statistics For Dummies

CERN Document Server

Rumsey, Deborah

2011-01-01

The fun and easy way to get down to business with statistics Stymied by statistics? No fear ? this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life. Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more.Tracks to a typical first semester statistics cou

A novel statistic for genome-wide interaction analysis.

Directory of Open Access Journals (Sweden)

Xuesen Wu

2010-09-01

Full Text Available Although great progress in genome-wide association studies (GWAS has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked. The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDR<0.001 and 0.001statistic is able to search significant interaction between SNPs across the genome. Real data analysis showed that the results of genome-wide interaction analysis can be replicated in two independent studies.

Descriptive statistics.

Science.gov (United States)

Nick, Todd G

2007-01-01

Statistics is defined by the Medical Subject Headings (MeSH) thesaurus as the science and art of collecting, summarizing, and analyzing data that are subject to random variation. The two broad categories of summarizing and analyzing data are referred to as descriptive and inferential statistics. This chapter considers the science and art of summarizing data where descriptive statistics and graphics are used to display data. In this chapter, we discuss the fundamentals of descriptive statistics, including describing qualitative and quantitative variables. For describing quantitative variables, measures of location and spread, for example the standard deviation, are presented along with graphical presentations. We also discuss distributions of statistics, for example the variance, as well as the use of transformations. The concepts in this chapter are useful for uncovering patterns within the data and for effectively presenting the results of a project.

Statistical Power in Plant Pathology Research.

Science.gov (United States)

Gent, David H; Esker, Paul D; Kriss, Alissa B

2018-01-01

In null hypothesis testing, failure to reject a null hypothesis may have two potential interpretations. One interpretation is that the treatments being evaluated do not have a significant effect, and a correct conclusion was reached in the analysis. Alternatively, a treatment effect may have existed but the conclusion of the study was that there was none. This is termed a Type II error, which is most likely to occur when studies lack sufficient statistical power to detect a treatment effect. In basic terms, the power of a study is the ability to identify a true effect through a statistical test. The power of a statistical test is 1 - (the probability of Type II errors), and depends on the size of treatment effect (termed the effect size), variance, sample size, and significance criterion (the probability of a Type I error, α). Low statistical power is prevalent in scientific literature in general, including plant pathology. However, power is rarely reported, creating uncertainty in the interpretation of nonsignificant results and potentially underestimating small, yet biologically significant relationships. The appropriate level of power for a study depends on the impact of Type I versus Type II errors and no single level of power is acceptable for all purposes. Nonetheless, by convention 0.8 is often considered an acceptable threshold and studies with power less than 0.5 generally should not be conducted if the results are to be conclusive. The emphasis on power analysis should be in the planning stages of an experiment. Commonly employed strategies to increase power include increasing sample sizes, selecting a less stringent threshold probability for Type I errors, increasing the hypothesized or detectable effect size, including as few treatment groups as possible, reducing measurement variability, and including relevant covariates in analyses. Power analysis will lead to more efficient use of resources and more precisely structured hypotheses, and may even

Statistical inference for template aging

Science.gov (United States)

Schuckers, Michael E.

2006-04-01

A change in classification error rates for a biometric device is often referred to as template aging. Here we offer two methods for determining whether the effect of time is statistically significant. The first of these is the use of a generalized linear model to determine if these error rates change linearly over time. This approach generalizes previous work assessing the impact of covariates using generalized linear models. The second approach uses of likelihood ratio tests methodology. The focus here is on statistical methods for estimation not the underlying cause of the change in error rates over time. These methodologies are applied to data from the National Institutes of Standards and Technology Biometric Score Set Release 1. The results of these applications are discussed.

Testing statistical self-similarity in the topology of river networks

Science.gov (United States)

Troutman, Brent M.; Mantilla, Ricardo; Gupta, Vijay K.

2010-01-01

Recent work has demonstrated that the topological properties of real river networks deviate significantly from predictions of Shreve's random model. At the same time the property of mean self-similarity postulated by Tokunaga's model is well supported by data. Recently, a new class of network model called random self-similar networks (RSN) that combines self-similarity and randomness has been introduced to replicate important topological features observed in real river networks. We investigate if the hypothesis of statistical self-similarity in the RSN model is supported by data on a set of 30 basins located across the continental United States that encompass a wide range of hydroclimatic variability. We demonstrate that the generators of the RSN model obey a geometric distribution, and self-similarity holds in a statistical sense in 26 of these 30 basins. The parameters describing the distribution of interior and exterior generators are tested to be statistically different and the difference is shown to produce the well-known Hack's law. The inter-basin variability of RSN parameters is found to be statistically significant. We also test generator dependence on two climatic indices, mean annual precipitation and radiative index of dryness. Some indication of climatic influence on the generators is detected, but this influence is not statistically significant with the sample size available. Finally, two key applications of the RSN model to hydrology and geomorphology are briefly discussed.

Gene cluster statistics with gene families.

Science.gov (United States)

Raghupathy, Narayanan; Durand, Dannie

2009-05-01

Identifying genomic regions that descended from a common ancestor is important for understanding the function and evolution of genomes. In distantly related genomes, clusters of homologous gene pairs are evidence of candidate homologous regions. Demonstrating the statistical significance of such "gene clusters" is an essential component of comparative genomic analyses. However, currently there are no practical statistical tests for gene clusters that model the influence of the number of homologs in each gene family on cluster significance. In this work, we demonstrate empirically that failure to incorporate gene family size in gene cluster statistics results in overestimation of significance, leading to incorrect conclusions. We further present novel analytical methods for estimating gene cluster significance that take gene family size into account. Our methods do not require complete genome data and are suitable for testing individual clusters found in local regions, such as contigs in an unfinished assembly. We consider pairs of regions drawn from the same genome (paralogous clusters), as well as regions drawn from two different genomes (orthologous clusters). Determining cluster significance under general models of gene family size is computationally intractable. By assuming that all gene families are of equal size, we obtain analytical expressions that allow fast approximation of cluster probabilities. We evaluate the accuracy of this approximation by comparing the resulting gene cluster probabilities with cluster probabilities obtained by simulating a realistic, power-law distributed model of gene family size, with parameters inferred from genomic data. Surprisingly, despite the simplicity of the underlying assumption, our method accurately approximates the true cluster probabilities. It slightly overestimates these probabilities, yielding a conservative test. We present additional simulation results indicating the best choice of parameter values for data

Statistical modeling of an integrated boiler for coal fired thermal power plant

Directory of Open Access Journals (Sweden)

Sreepradha Chandrasekharan

2017-06-01

Full Text Available The coal fired thermal power plants plays major role in the power production in the world as they are available in abundance. Many of the existing power plants are based on the subcritical technology which can produce power with the efficiency of around 33%. But the newer plants are built on either supercritical or ultra-supercritical technology whose efficiency can be up to 50%. Main objective of the work is to enhance the efficiency of the existing subcritical power plants to compensate for the increasing demand. For achieving the objective, the statistical modeling of the boiler units such as economizer, drum and the superheater are initially carried out. The effectiveness of the developed models is tested using analysis methods like R2 analysis and ANOVA (Analysis of Variance. The dependability of the process variable (temperature on different manipulated variables is analyzed in the paper. Validations of the model are provided with their error analysis. Response surface methodology (RSM supported by DOE (design of experiments are implemented to optimize the operating parameters. Individual models along with the integrated model are used to study and design the predictive control of the coal-fired thermal power plant. Keywords: Chemical engineering, Applied mathematics

Statistical versus Musical Significance: Commentary on Leigh VanHandel's 'National Metrical Types in Nineteenth Century Art Song'

Directory of Open Access Journals (Sweden)

Justin London

2010-01-01

Full Text Available In “National Metrical Types in Nineteenth Century Art Song” Leigh Van Handel gives a sympathetic critique of William Rothstein’s claim that in western classical music of the late 18th and 19th centuries there are discernable differences in the phrasing and metrical practice of German versus French and Italian composers. This commentary (a examines just what Rothstein means in terms of his proposed metrical typology, (b questions Van Handel on how she has applied it to a purely melodic framework, (c amplifies Van Handel’s critique of Rothstein, and then (d concludes with a rumination on the reach of quantitative (i.e., statistically-driven versus qualitative claims regarding such things as “national metrical types.”

Statistical characterization report for Single-Shell Tank 241-T-107

International Nuclear Information System (INIS)

Cromar, R.D.; Wilmarth, S.R.; Jensen, L.

1994-01-01

This report contains the results of the statistical analysis of data from three core samples obtained from single-shell tank 241-T-107 (T-107). Four specific topics are addressed. They are summarized below. Section 3.0 contains mean concentration estimates of analytes found in T-107. The estimates of open-quotes errorclose quotes associated with the concentration estimates are given as 95% confidence intervals (CI) on the mean. The results given are based on three types of samples: core composite samples, core segment samples, and drainable liquid samples. Section 4.0 contains estimates of the spatial variability (variability between cores and between segments) and the analytical variability (variability between the primary and the duplicate analysis). Statistical tests were performed to test the hypothesis that the between cores and the between segments spatial variability is zero. The results of the tests are as follows. Based on the core composite data, the between cores variance is significantly different from zero for 35 out of 74 analytes; i.e., for 53% of the analytes there is no statistically significant difference between the concentration means for two cores. Based on core segment data, the between segments variance is significantly different from zero for 22 out of 24 analytes and the between cores variance is significantly different from zero for 4 out of 24 analytes; i.e., for 8% of the analytes there is no statistically significant difference between segment means and for 83% of the analytes there is no difference between the means from the three cores. Section 5.0 contains the results of the application of multiple comparison methods to the core composite data, the core segment data, and the drainable liquid data. Section 6.0 contains the results of a statistical test conducted to determine the 222-S Analytical Laboratory's ability to homogenize solid core segments

Statistics in Schools

Science.gov (United States)

Information Statistics in Schools Educate your students about the value and everyday use of statistics. The Statistics in Schools program provides resources for teaching and learning with real life data. Explore the site for standards-aligned, classroom-ready activities. Statistics in Schools Math Activities History

The effect of Kinesio Taping on postural control in subjects with non-specific chronic low back pain.

Science.gov (United States)

Abbasi, Soheila; Rojhani-Shirazi, Zahra; Shokri, Esmaeil; García-Muro San José, Francisco

2018-04-01

The aim of this study was to investigate the possible alterations in postural control during upright standing in subjects with non-specific chronic low back pain and the effect of Kinesio taping on the postural control. Twenty subjects with non-specific chronic low back pain and twenty healthy subjects participated in this study. The center of pressure excursion was evaluated before the intervention for both groups, and immediately after intervention for the low back pain group. Independent sample t-test, Mann-Whitney test and repeated measure ANOVA were used for the statistical analysis of the data. There were significant differences in the center of pressure excursion between the low back pain group versus the healthy group. The results of the ANOVA demonstrated a statistically significant difference in the mean COP displacement and velocity before Kinesio Taping, immediately after, and 24 h after in the low back pain group. There are poor postural control mechanisms in subjects with non-specific chronic low back pain. Kinesio taping seems to change postural control immediately and have lasting effects until the day after. Copyright © 2017 Elsevier Ltd. All rights reserved.

Impact of idpn on kt/v

Directory of Open Access Journals (Sweden)

Dukkipati R

2012-06-01

A repeated measures ANOVA indicated a statistically significant difference (p<0.0001. A Tukey’s adjustment resulted in non-significant differences between month 1 and month 2 (p=0.995, month 1 and month 3 (p=0.987, and month 2 and month 3 (p=0.936. In conclusion, the initial decrease in Kt/V was followed by a period of stabilization, and the mean Kt/V never dropped below the KDOQI recommendation of 1.2.

Cluster size statistic and cluster mass statistic: two novel methods for identifying changes in functional connectivity between groups or conditions.

Science.gov (United States)

Ing, Alex; Schwarzbauer, Christian

2014-01-01

Functional connectivity has become an increasingly important area of research in recent years. At a typical spatial resolution, approximately 300 million connections link each voxel in the brain with every other. This pattern of connectivity is known as the functional connectome. Connectivity is often compared between experimental groups and conditions. Standard methods used to control the type 1 error rate are likely to be insensitive when comparisons are carried out across the whole connectome, due to the huge number of statistical tests involved. To address this problem, two new cluster based methods--the cluster size statistic (CSS) and cluster mass statistic (CMS)--are introduced to control the family wise error rate across all connectivity values. These methods operate within a statistical framework similar to the cluster based methods used in conventional task based fMRI. Both methods are data driven, permutation based and require minimal statistical assumptions. Here, the performance of each procedure is evaluated in a receiver operator characteristic (ROC) analysis, utilising a simulated dataset. The relative sensitivity of each method is also tested on real data: BOLD (blood oxygen level dependent) fMRI scans were carried out on twelve subjects under normal conditions and during the hypercapnic state (induced through the inhalation of 6% CO2 in 21% O2 and 73%N2). Both CSS and CMS detected significant changes in connectivity between normal and hypercapnic states. A family wise error correction carried out at the individual connection level exhibited no significant changes in connectivity.

Mathematical and statistical analysis of the effect of boron on yield parameters of wheat

Energy Technology Data Exchange (ETDEWEB)

Rawashdeh, Hamzeh [Water Management and Environment Research Department, National Center for Agricultural Research and Extension, P.O. Box 639, Baqa 19381 (Jordan); Sala, Florin [Soil Science and Plant Nutrition, Faculty of Agriculture, Banat University of Agricultural Sciences and Veterinary Medicine “Regele Mihai I al României” from Timişoara, Timişoara, 300645 (Romania); Boldea, Marius [Mathematics and Statistics, Faculty of Agriculture, Banat University of Agricultural Sciences and Veterinary Medicine “Regele Mihai I al României” from Timisoara, Timişoara, 300645 (Romania)

2015-03-10

The main objective of this research is to investigate the effect of foliar applications of boron at different growth stages on yield and yield parameters of wheat. The contribution of boron in achieving yield parameters is described by second degree polynomial equations, with high statistical confidence (p<0.01; F theoretical < F calculated, according to ANOVA test, for Alfa = 0.05). Regression analysis, based on R{sup 2} values obtained, made it possible to evaluate the particular contribution of boron to the realization of yield parameters. This was lower for spike length (R{sup 2} = 0.812), thousand seeds weight (R{sup 2} = 0.850) and higher in the case of the number of spikelets (R{sup 2} = 0.936) and the number of seeds on a spike (R{sup 2} = 0.960). These results confirm that boron plays an important part in achieving the number of seeds on a spike in the case of wheat, as the contribution of this element to the process of flower fertilization is well-known. In regards to productivity elements, the contribution of macroelements to yield quantity is clear, the contribution of B alone being R{sup 2} = 0.868.

Statistical Damage Detection of Civil Engineering Structures using ARMAV Models

DEFF Research Database (Denmark)

Andersen, P.; Kirkegaard, Poul Henning

In this paper a statistically based damage detection of a lattice steel mast is performed. By estimation of the modal parameters and their uncertainties it is possible to detect whether some of the modal parameters have changed with a statistical significance. The estimation of the uncertainties ...

Clinicopathological significance of c-MYC in esophageal squamous cell carcinoma.

Science.gov (United States)

Lian, Yu; Niu, Xiangdong; Cai, Hui; Yang, Xiaojun; Ma, Haizhong; Ma, Shixun; Zhang, Yupeng; Chen, Yifeng

2017-07-01

Esophageal squamous cell carcinoma is one of the most common malignant tumors. The oncogene c-MYC is thought to be important in the initiation, promotion, and therapy resistance of cancer. In this study, we aim to investigate the clinicopathologic roles of c-MYC in esophageal squamous cell carcinoma tissue. This study is aimed at discovering and analyzing c-MYC expression in a series of human esophageal tissues. A total of 95 esophageal squamous cell carcinoma samples were analyzed by the western blotting and immunohistochemistry techniques. Then, correlation of c-MYC expression with clinicopathological features of esophageal squamous cell carcinoma patients was statistically analyzed. In most esophageal squamous cell carcinoma cases, the c-MYC expression was positive in tumor tissues. The positive rate of c-MYC expression in tumor tissues was 61.05%, obviously higher than the adjacent normal tissues (8.42%, 8/92) and atypical hyperplasia tissues (19.75%, 16/95). There was a statistical difference among adjacent normal tissues, atypical hyperplasia tissues, and tumor tissues. Overexpression of the c-MYC was detected in 61.05% (58/95) esophageal squamous cell carcinomas, which was significantly correlated with the degree of differentiation (p = 0.004). The positive rate of c-MYC expression was 40.0% in well-differentiated esophageal tissues, with a significantly statistical difference (p = 0.004). The positive rate of c-MYC was 41.5% in T1 + T2 esophageal tissues and 74.1% in T3 + T4 esophageal tissues, with a significantly statistical difference (p = 0.001). The positive rate of c-MYC was 45.0% in I + II esophageal tissues and 72.2% in III + IV esophageal tissues, with a significantly statistical difference (p = 0.011). The c-MYC expression strongly correlated with clinical staging (p = 0.011), differentiation degree (p = 0.004), lymph node metastasis (p = 0.003), and invasion depth (p = 0.001) of patients with esophageal squamous cell carcinoma. The c-MYC was

Optimization of significant insolation distribution parameters - A new approach towards BIPV system design

Energy Technology Data Exchange (ETDEWEB)

Paul, D. [SSBB and Senior Member-ASQ, Kolkata (India); Mandal, S.N. [Kalyani Govt Engg College, Kalyani (India); Mukherjee, D.; Bhadra Chaudhuri, S.R. [Dept of E. and T. C. Engg, B.E.S.U., Shibpur (India)

2010-10-15

System efficiency and payback time are yet to attain a commercially viable level for solar photovoltaic energy projects. Despite huge development in prediction of solar radiation data, there is a gap in extraction of pertinent information from such data. Hence the available data cannot be effectively utilized for engineering application. This is acting as a barrier for the emerging technology. For making accurate engineering and financial calculations regarding any solar energy project, it is crucial to identify and optimize the most significant statistic(s) representing insolation availability by the Photovoltaic setup at the installation site. Quality Function Deployment (QFD) technique has been applied for identifying the statistic(s), which are of high significance from a project designer's point of view. A MATLAB trademark program has been used to build the annual frequency distribution of hourly insolation over any module plane at a given location. Descriptive statistical analysis of such distributions is done through MINITAB trademark. For Building Integrated Photo Voltaic (BIPV) installation, similar statistical analysis has been carried out for the composite frequency distribution, which is formed by weighted summation of insolation distributions for different module planes used in the installation. Vital most influential statistic(s) of the composite distribution have been optimized through Artificial Neural Network computation. This approach is expected to open up a new horizon in BIPV system design. (author)

PRIS-STATISTICS: Power Reactor Information System Statistical Reports. User's Manual

International Nuclear Information System (INIS)

2013-01-01

The IAEA developed the Power Reactor Information System (PRIS)-Statistics application to assist PRIS end users with generating statistical reports from PRIS data. Statistical reports provide an overview of the status, specification and performance results of every nuclear power reactor in the world. This user's manual was prepared to facilitate the use of the PRIS-Statistics application and to provide guidelines and detailed information for each report in the application. Statistical reports support analyses of nuclear power development and strategies, and the evaluation of nuclear power plant performance. The PRIS database can be used for comprehensive trend analyses and benchmarking against best performers and industrial standards.

Statistical physics

CERN Document Server

Sadovskii, Michael V

2012-01-01

This volume provides a compact presentation of modern statistical physics at an advanced level. Beginning with questions on the foundations of statistical mechanics all important aspects of statistical physics are included, such as applications to ideal gases, the theory of quantum liquids and superconductivity and the modern theory of critical phenomena. Beyond that attention is given to new approaches, such as quantum field theory methods and non-equilibrium problems.

Behavioral investment strategy matters: a statistical arbitrage approach

OpenAIRE

Sun, David; Tsai, Shih-Chuan; Wang, Wei

2011-01-01

In this study, we employ a statistical arbitrage approach to demonstrate that momentum investment strategy tend to work better in periods longer than six months, a result different from findings in past literature. Compared with standard parametric tests, the statistical arbitrage method produces more clearly that momentum strategies work only in longer formation and holding periods. Also they yield positive significant returns in an up market, but negative yet insignificant returns in a down...

Comparing identified and statistically significant lipids and polar metabolites in 15-year old serum and dried blood spot samples for longitudinal studies: Comparing lipids and metabolites in serum and DBS samples

Energy Technology Data Exchange (ETDEWEB)

Kyle, Jennifer E. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Casey, Cameron P. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Stratton, Kelly G. [National Security Directorate, Pacific Northwest National Laboratory, Richland WA USA; Zink, Erika M. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Kim, Young-Mo [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Zheng, Xueyun [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Monroe, Matthew E. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Weitz, Karl K. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Bloodsworth, Kent J. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Orton, Daniel J. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Ibrahim, Yehia M. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Moore, Ronald J. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Lee, Christine G. [Department of Medicine, Bone and Mineral Unit, Oregon Health and Science University, Portland OR USA; Research Service, Portland Veterans Affairs Medical Center, Portland OR USA; Pedersen, Catherine [Department of Medicine, Bone and Mineral Unit, Oregon Health and Science University, Portland OR USA; Orwoll, Eric [Department of Medicine, Bone and Mineral Unit, Oregon Health and Science University, Portland OR USA; Smith, Richard D. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Burnum-Johnson, Kristin E. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Baker, Erin S. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA

2017-02-05

The use of dried blood spots (DBS) has many advantages over traditional plasma and serum samples such as smaller blood volume required, storage at room temperature, and ability for sampling in remote locations. However, understanding the robustness of different analytes in DBS samples is essential, especially in older samples collected for longitudinal studies. Here we analyzed DBS samples collected in 2000-2001 and stored at room temperature and compared them to matched serum samples stored at -80°C to determine if they could be effectively used as specific time points in a longitudinal study following metabolic disease. Four hundred small molecules were identified in both the serum and DBS samples using gas chromatograph-mass spectrometry (GC-MS), liquid chromatography-MS (LC-MS) and LC-ion mobility spectrometry-MS (LC-IMS-MS). The identified polar metabolites overlapped well between the sample types, though only one statistically significant polar metabolite in a case-control study was conserved, indicating degradation occurs in the DBS samples affecting quantitation. Differences in the lipid identifications indicated that some oxidation occurs in the DBS samples. However, thirty-six statistically significant lipids correlated in both sample types indicating that lipid quantitation was more stable across the sample types.

T2 relaxation time is related to liver fibrosis severity

Science.gov (United States)

Siqueira, Luiz; Uppal, Ritika; Alford, Jamu; Fuchs, Bryan C.; Yamada, Suguru; Tanabe, Kenneth; Chung, Raymond T.; Lauwers, Gregory; Chew, Michael L.; Boland, Giles W.; Sahani, Duhyant V.; Vangel, Mark; Hahn, Peter F.; Caravan, Peter

2016-01-01

echo T2 weighted data. Statistical comparison was performed using ANOVA. Results (I) Histopathologic evaluation of both rat and human livers demonstrated no evidence of steatosis or hemochromatosis There was a monotonic increase in mean T2 value with increasing degree of fibrosis (control 65.4±2.9 ms, n=6 patients); mild (Ishak 1–2) 66.7±1.9 ms (n=30); moderate (Ishak 3–4) 71.6±1.7 ms (n=26); severe (Ishak 5–6) 72.4±1.4 ms (n=61); with relatively low standard error (~2.9 ms). There was a statistically significant difference between degrees of mild (Ishak fibrosis (Ishak >4) (P=0.03) based on logistic regression of T2 and Ishak, which became insignificant (P=0.07) when using inflammatory markers as covariates. Expanding on this model using ordinal logistic regression, there was significance amongst all 4 groups comparing T2 to Ishak (P=0.01), with significance using inflammation as a covariate (P=0.03) and approaching statistical significance amongst all groups by ANOVA (P=0.07); (II) there was a monotonic increase in T2 and statistical significance (ANOVA Pliver (e.g., 20–100 ms), demonstrated no statistical difference between two point fits on turbo spin echo (TSE) data and multi-echo CPMG data (P=0.9). Conclusions The finding of increased T2 with liver fibrosis may relate to inflammation that may be an alternative or adjunct to other noninvasive MR imaging based approaches for assessing liver fibrosis. PMID:27190762

Bose and his statistics

International Nuclear Information System (INIS)

Venkataraman, G.

1992-01-01

Treating radiation gas as a classical gas, Einstein derived Planck's law of radiation by considering the dynamic equilibrium between atoms and radiation. Dissatisfied with this treatment, S.N. Bose derived Plank's law by another original way. He treated the problem in generality: he counted how many cells were available for the photon gas in phase space and distributed the photons into these cells. In this manner of distribution, there were three radically new ideas: The indistinguishability of particles, the spin of the photon (with only two possible orientations) and the nonconservation of photon number. This gave rise to a new discipline of quantum statistical mechanics. Physics underlying Bose's discovery, its significance and its role in development of the concept of ideal gas, spin-statistics theorem and spin particles are described. The book has been written in a simple and direct language in an informal style aiming to stimulate the curiosity of a reader. (M.G.B.)

Statistical trend analysis methodology for rare failures in changing technical systems

International Nuclear Information System (INIS)

Ott, K.O.; Hoffmann, H.J.

1983-07-01

A methodology for a statistical trend analysis (STA) in failure rates is presented. It applies primarily to relatively rare events in changing technologies or components. The formulation is more general and the assumptions are less restrictive than in a previously published version. Relations of the statistical analysis and probabilistic assessment (PRA) are discussed in terms of categorization of decisions for action following particular failure events. The significance of tentatively identified trends is explored. In addition to statistical tests for trend significance, a combination of STA and PRA results quantifying the trend complement is proposed. The STA approach is compared with other concepts for trend characterization. (orig.)

Statistical distribution for generalized ideal gas of fractional-statistics particles

International Nuclear Information System (INIS)

Wu, Y.

1994-01-01

We derive the occupation-number distribution in a generalized ideal gas of particles obeying fractional statistics, including mutual statistics, by adopting a state-counting definition. When there is no mutual statistics, the statistical distribution interpolates between bosons and fermions, and respects a fractional exclusion principle (except for bosons). Anyons in a strong magnetic field at low temperatures constitute such a physical system. Applications to the thermodynamic properties of quasiparticle excitations in the Laughlin quantum Hall fluid are discussed

Childhood Cancer Statistics

Science.gov (United States)

... Watchdog Ratings Feedback Contact Select Page Childhood Cancer Statistics Home > Cancer Resources > Childhood Cancer Statistics Childhood Cancer Statistics – Graphs and Infographics Number of Diagnoses Incidence Rates ...

Are studies reporting significant results more likely to be published?

Science.gov (United States)

Koletsi, Despina; Karagianni, Anthi; Pandis, Nikolaos; Makou, Margarita; Polychronopoulou, Argy; Eliades, Theodore

2009-11-01

Our objective was to assess the hypothesis that there are variations of the proportion of articles reporting a significant effect, with a higher percentage of those articles published in journals with impact factors. The contents of 5 orthodontic journals (American Journal of Orthodontics and Dentofacial Orthopedics, Angle Orthodontist, European Journal of Orthodontics, Journal of Orthodontics, and Orthodontics and Craniofacial Research), published between 2004 and 2008, were hand-searched. Articles with statistical analysis of data were included in the study and classified into 4 categories: behavior and psychology, biomaterials and biomechanics, diagnostic procedures and treatment, and craniofacial growth, morphology, and genetics. In total, 2622 articles were examined, with 1785 included in the analysis. Univariate and multivariate logistic regression analyses were applied with statistical significance as the dependent variable, and whether the journal had an impact factor, the subject, and the year were the independent predictors. A higher percentage of articles showed significant results relative to those without significant associations (on average, 88% vs 12%) for those journals. Overall, these journals published significantly more studies with significant results, ranging from 75% to 90% (P = 0.02). Multivariate modeling showed that journals with impact factors had a 100% increased probability of publishing a statistically significant result compared with journals with no impact factor (odds ratio [OR], 1.99; 95% CI, 1.19-3.31). Compared with articles on biomaterials and biomechanics, all other subject categories showed lower probabilities of significant results. Nonsignificant findings in behavior and psychology and diagnosis and treatment were 1.8 (OR, 1.75; 95% CI, 1.51-2.67) and 3.5 (OR, 3.50; 95% CI, 2.27-5.37) times more likely to be published, respectively. Journals seem to prefer reporting significant results; this might be because of authors

Critical analysis of adsorption data statistically

Science.gov (United States)

Kaushal, Achla; Singh, S. K.

2017-10-01

Experimental data can be presented, computed, and critically analysed in a different way using statistics. A variety of statistical tests are used to make decisions about the significance and validity of the experimental data. In the present study, adsorption was carried out to remove zinc ions from contaminated aqueous solution using mango leaf powder. The experimental data was analysed statistically by hypothesis testing applying t test, paired t test and Chi-square test to (a) test the optimum value of the process pH, (b) verify the success of experiment and (c) study the effect of adsorbent dose in zinc ion removal from aqueous solutions. Comparison of calculated and tabulated values of t and χ 2 showed the results in favour of the data collected from the experiment and this has been shown on probability charts. K value for Langmuir isotherm was 0.8582 and m value for Freundlich adsorption isotherm obtained was 0.725, both are mango leaf powder.

Can Money Buy Happiness? A Statistical Analysis of Predictors for User Satisfaction

Science.gov (United States)

Hunter, Ben; Perret, Robert

2011-01-01

2007 data from LibQUAL+[TM] and the ACRL Library Trends and Statistics database were analyzed to determine if there is a statistically significant correlation between library expenditures and usage statistics and library patron satisfaction across 73 universities. The results show that users of larger, better funded libraries have higher…

Nonparametric statistical inference

CERN Document Server

Gibbons, Jean Dickinson

2010-01-01

Overall, this remains a very fine book suitable for a graduate-level course in nonparametric statistics. I recommend it for all people interested in learning the basic ideas of nonparametric statistical inference.-Eugenia Stoimenova, Journal of Applied Statistics, June 2012… one of the best books available for a graduate (or advanced undergraduate) text for a theory course on nonparametric statistics. … a very well-written and organized book on nonparametric statistics, especially useful and recommended for teachers and graduate students.-Biometrics, 67, September 2011This excellently presente

Statistics for Research

CERN Document Server

Dowdy, Shirley; Chilko, Daniel

2011-01-01

Praise for the Second Edition "Statistics for Research has other fine qualities besides superior organization. The examples and the statistical methods are laid out with unusual clarity by the simple device of using special formats for each. The book was written with great care and is extremely user-friendly."-The UMAP Journal Although the goals and procedures of statistical research have changed little since the Second Edition of Statistics for Research was published, the almost universal availability of personal computers and statistical computing application packages have made it possible f

Head First Statistics

CERN Document Server

Griffiths, Dawn

2009-01-01

Wouldn't it be great if there were a statistics book that made histograms, probability distributions, and chi square analysis more enjoyable than going to the dentist? Head First Statistics brings this typically dry subject to life, teaching you everything you want and need to know about statistics through engaging, interactive, and thought-provoking material, full of puzzles, stories, quizzes, visual aids, and real-world examples. Whether you're a student, a professional, or just curious about statistical analysis, Head First's brain-friendly formula helps you get a firm grasp of statistics

Gut-directed hypnotherapy significantly augments clinical remission in quiescent ulcerative colitis

Science.gov (United States)

Keefer, Laurie; Taft, Tiffany H; Kiebles, Jennifer L; Martinovich, Zoran; Barrett, Terrence A; Palsson, Olafur S

2013-01-01

Summary Background Psychotherapy is not routinely recommended for in ulcerative colitis (UC). Gut-directed hypnotherapy (HYP) has been linked to improved function in the gastrointestinal tract and may operate through immune-mediated pathways in chronic diseases. Aims To determine the feasibility and acceptability of hypnotherapy and estimate the impact of hypnotherapy on clinical remission status over a 1 year period in patients with an historical flare rate of 1.3 times per year. Methods 54 patients were randomized at a single site to 7 sessions of gut-directed hypnotherapy (N = 26) or attention control (CON; N = 29) and followed for 1 year. The primary outcome was the proportion of participants in each condition that had remained clinically asymptomatic (clinical remission) through 52 weeks post-treatment. Results One-way ANOVA comparing hypnotherapy and control subjects on number of days to clinical relapse favored the hypnotherapy condition [F = 4.8 (1, 48), p = .03] by 78 days. Chi square analysis comparing the groups on proportion maintaining remission at 1 year was also significant [X2(1) = 3.9, p = .04], with 68% of hypnotherapy and 40% of control patients maintaining remission for 1 year. There were no significant differences between groups over time in quality of life, medication adherence, perceived stress or psychological factors. Conclusions This is the first prospective study that has demonstrated a significant effect of a psychological intervention on prolonging clinical remission in patients with quiescent UC. Clinical Trial # NCT00798642 PMID:23957526

A Nineteenth Century Statistical Society that Abandoned Statistics

NARCIS (Netherlands)

Stamhuis, I.H.

2007-01-01

In 1857, a Statistical Society was founded in the Netherlands. Within this society, statistics was considered a systematic, quantitative, and qualitative description of society. In the course of time, the society attracted a wide and diverse membership, although the number of physicians on its rolls

IGESS: a statistical approach to integrating individual-level genotype data and summary statistics in genome-wide association studies.

Science.gov (United States)

Dai, Mingwei; Ming, Jingsi; Cai, Mingxuan; Liu, Jin; Yang, Can; Wan, Xiang; Xu, Zongben

2017-09-15

Results from genome-wide association studies (GWAS) suggest that a complex phenotype is often affected by many variants with small effects, known as 'polygenicity'. Tens of thousands of samples are often required to ensure statistical power of identifying these variants with small effects. However, it is often the case that a research group can only get approval for the access to individual-level genotype data with a limited sample size (e.g. a few hundreds or thousands). Meanwhile, summary statistics generated using single-variant-based analysis are becoming publicly available. The sample sizes associated with the summary statistics datasets are usually quite large. How to make the most efficient use of existing abundant data resources largely remains an open question. In this study, we propose a statistical approach, IGESS, to increasing statistical power of identifying risk variants and improving accuracy of risk prediction by i ntegrating individual level ge notype data and s ummary s tatistics. An efficient algorithm based on variational inference is developed to handle the genome-wide analysis. Through comprehensive simulation studies, we demonstrated the advantages of IGESS over the methods which take either individual-level data or summary statistics data as input. We applied IGESS to perform integrative analysis of Crohns Disease from WTCCC and summary statistics from other studies. IGESS was able to significantly increase the statistical power of identifying risk variants and improve the risk prediction accuracy from 63.2% ( ±0.4% ) to 69.4% ( ±0.1% ) using about 240 000 variants. The IGESS software is available at https://github.com/daviddaigithub/IGESS . zbxu@xjtu.edu.cn or xwan@comp.hkbu.edu.hk or eeyang@hkbu.edu.hk. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Statistics for economics

CERN Document Server

Naghshpour, Shahdad

2012-01-01

Statistics is the branch of mathematics that deals with real-life problems. As such, it is an essential tool for economists. Unfortunately, the way you and many other economists learn the concept of statistics is not compatible with the way economists think and learn. The problem is worsened by the use of mathematical jargon and complex derivations. Here's a book that proves none of this is necessary. All the examples and exercises in this book are constructed within the field of economics, thus eliminating the difficulty of learning statistics with examples from fields that have no relation to business, politics, or policy. Statistics is, in fact, not more difficult than economics. Anyone who can comprehend economics can understand and use statistics successfully within this field, including you! This book utilizes Microsoft Excel to obtain statistical results, as well as to perform additional necessary computations. Microsoft Excel is not the software of choice for performing sophisticated statistical analy...

Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation

Science.gov (United States)

Sharma, Manali; Das, Kamalika; Bilgic, Mustafa; Matthews, Bryan; Nielsen, David Lynn; Oza, Nikunj C.

2016-01-01

A major focus of the commercial aviation community is discovery of unknown safety events in flight operations data. Data-driven unsupervised anomaly detection methods are better at capturing unknown safety events compared to rule-based methods which only look for known violations. However, not all statistical anomalies that are discovered by these unsupervised anomaly detection methods are operationally significant (e.g., represent a safety concern). Subject Matter Experts (SMEs) have to spend significant time reviewing these statistical anomalies individually to identify a few operationally significant ones. In this paper we propose an active learning algorithm that incorporates SME feedback in the form of rationales to build a classifier that can distinguish between uninteresting and operationally significant anomalies. Experimental evaluation on real aviation data shows that our approach improves detection of operationally significant events by as much as 75% compared to the state-of-the-art. The learnt classifier also generalizes well to additional validation data sets.

Prevalence of significant bacteriuria among symptomatic and ...

African Journals Online (AJOL)

Data were analyzed using the Statistical Package for Social Sciences (SPSS) version 16.0 (SPSS, Inc., Chicago, Ill). Results: A total of 100 consenting participants were recruited into the study. The mean age was: 23.42 ± 8.31 years and a range of 14‑50 years. Only 9% (9/100) had significant bacteriuria while 44.4% (4/9) ...

Comparison of shear bond strength of four types of orthodontic brackets with different base technologies

Directory of Open Access Journals (Sweden)

Gaurang H Chaudhary

2017-01-01

Full Text Available Objectives: The aim of this study was to compare the shear bond strength (SBS of brackets systems with four different base technologies. Materials and Methods: Maxillary first premolars were randomly divided into four groups of thirty specimens each: (1 Master Series™ conventional twin, (2 T3™ self-ligating, (3 Victory series™ conventional twin, and (4 H4™ self-ligating brackets. Maxillary first premolars were bracketed using an acid-etch composite system, and the SBS measured using an Instron Universal Testing Machine at a crosshead speed of 2 mm/min. The ANOVA and Tukey's multiple comparison tests were performed with significance predetermined at P ≤ 0.05. Results: The overall mean bond strengths were 8.49 ± 2.93, 10.85 ± 3.34, 9.42 ± 2.97, and 9.73 ± 2.62 for the Groups 1, 2, 3, and 4 brackets, respectively. One-way ANOVA test gave an F = 3.182 with a P = 0.026. The Group 1 and Group 2 were observed to have statistically significant difference with a P = 0.014. Conclusions: The T3 self-ligating one-piece design with microetched Quadra Grip™ base brackets had the highest bond strength. The SBS difference between Group 2, Group 3, and Group 4 was not significant, but the difference between Group 2 and Group 1 was statistically significant.

Understanding and forecasting polar stratospheric variability with statistical models

Directory of Open Access Journals (Sweden)

C. Blume

2012-07-01

Full Text Available The variability of the north-polar stratospheric vortex is a prominent aspect of the middle atmosphere. This work investigates a wide class of statistical models with respect to their ability to model geopotential and temperature anomalies, representing variability in the polar stratosphere. Four partly nonstationary, nonlinear models are assessed: linear discriminant analysis (LDA; a cluster method based on finite elements (FEM-VARX; a neural network, namely the multi-layer perceptron (MLP; and support vector regression (SVR. These methods model time series by incorporating all significant external factors simultaneously, including ENSO, QBO, the solar cycle, volcanoes, to then quantify their statistical importance. We show that variability in reanalysis data from 1980 to 2005 is successfully modeled. The period from 2005 to 2011 can be hindcasted to a certain extent, where MLP performs significantly better than the remaining models. However, variability remains that cannot be statistically hindcasted within the current framework, such as the unexpected major warming in January 2009. Finally, the statistical model with the best generalization performance is used to predict a winter 2011/12 with warm and weak vortex conditions. A vortex breakdown is predicted for late January, early February 2012.

Study of long term structural and functional changes in medically controlled glaucoma

Directory of Open Access Journals (Sweden)

Achyut N Pandey

2014-02-01

Full Text Available AIM:Prospectively analyze the long term structural and functional changes in patients of primary open angle glaucoma (POAG receiving medical therapy (beta blockers and non beta blockers. In this study an attempt has been made to evaluate whether medical reduction of IOP prevents or delays the progression of glaucomatous visual field loss and/or optic nerve damage in patients with open angle glaucoma.METHODS:Study conducted over a period of 27 months, at a tertiary eye care hospital including both eyes of 40 patients with POAG. Group 1 (20 patients, 40 eyes received beta-blockers, and Group 2 (20 patients, 40 eyes received non-beta-blockers. Each patient underwent intraocular pressure measurement, best corrected visual acuity, slit-lamp, fundus examination, gonioscopy, central corneal thickness, visual field assessment by Humphrey automated perimetry and retinal nerve fibre layer thickness by Stratus optical coherence tomography at baseline and at two subsequent visits. The average time interval between each visit was 10-11 months. The statistical analysis was done using one-way analysis of variance (ANOVA. Post-hoc test, using tukey’ method were adopted. Probablity (P value of 0.05 or less was considered to be statistically significant.RESULTS:A total of 80 eyes of 40 patients of POAG were enrolled, 24 males, 16 females, age group 50-80 years. In both beta and non beta blocker group, reduction (improvement in mean IOP from initial levels to the levels achieved at the 2nd and 3rd visits was statistically significant. One way ANOVA (df=2, fisher f value=11.64, P=0.000, one way ANOVA (df=3, fisher f value=35.61, P=0.000. Both mean deviation (MD and pattern standard deviation (PSD in both beta and non beta blockers at different visits were not statistically significant. Retinal nerve fibre layer thickness (RNFL -only mean inferior retinal nerve fibre layer, the difference between the mean value in beta and non beta blocker groupwere statistically

Analýza rozptylu v R

OpenAIRE

Švejdová, Klára

2015-01-01

The bachelor thesis focuses on the One-way ANOVA and its nonparametric counterpart the Kruskal-Wallis test. The aim of this bachelor thesis is to analyse the ANOVA's test validity and power in case of assumptions (e. g. normal distribution, homoscedasticity and sample size) violations. The conclusions of the One-way ANOVA are compared with the Kruskal-Wallis test. The analysis is performed using Monte Carlo simulations implemented in the statistical software R. Based on the simulations, it is...

Statistical data analysis using SAS intermediate statistical methods

CERN Document Server

Marasinghe, Mervyn G

2018-01-01

The aim of this textbook (previously titled SAS for Data Analytics) is to teach the use of SAS for statistical analysis of data for advanced undergraduate and graduate students in statistics, data science, and disciplines involving analyzing data. The book begins with an introduction beyond the basics of SAS, illustrated with non-trivial, real-world, worked examples. It proceeds to SAS programming and applications, SAS graphics, statistical analysis of regression models, analysis of variance models, analysis of variance with random and mixed effects models, and then takes the discussion beyond regression and analysis of variance to conclude. Pedagogically, the authors introduce theory and methodological basis topic by topic, present a problem as an application, followed by a SAS analysis of the data provided and a discussion of results. The text focuses on applied statistical problems and methods. Key features include: end of chapter exercises, downloadable SAS code and data sets, and advanced material suitab...

Neuroendocrine Tumor: Statistics

Science.gov (United States)

... Tumor > Neuroendocrine Tumor: Statistics Request Permissions Neuroendocrine Tumor: Statistics Approved by the Cancer.Net Editorial Board , 01/ ... the body. It is important to remember that statistics on the survival rates for people with a ...

Detection and significance of serum inflammatory factors and oxidative stress indicators in diabetic retinopathy

Institute of Scientific and Technical Information of China (English)

Wei Gao; Jing Wang; Chao Zhang; Ping Qin

2017-01-01

Objective:To determine the serum inflammatory cytokines and oxidative stress parameters of diabetic retinopathy (DR) patients to explore their possible role in the DR.Methods: 116 cases of type 2 diabetic patients were selected from June 2015 to June 2016 in our hospital as research subjects, divided into diabetic Diabetes without retinopathy (NDR group,n = 63) and diabetic with retinopathy patients (DR group,n = 53). And 60 cases of healthy check-ups of the same period in our hospital medical center were selected as normal control group (NC). The VEGF, IL-6, TNF-α , MDA and SOD levels of three groups of patients were detected. Results:The IL-6 levels of NC group, NDR group and DR group were increased gradually, and the difference was statistically significant (P<0.05). The TNF-α levels of NC group, NDR group and DR group were increased gradually, and the difference was statistically significant (P<0.05). The VEGF levels of NC group, NDR group and DR group were increased gradually, and the difference was statistically significant (P<0.05). The malondialdehyde (MDA) levels of NC group, NDR group and DR group increased gradually, and the difference was statistically significant (P<0.05). The superoxide dismutase (SOD) levels of NC group, NDR group and DR group were decreased gradually, and the difference was statistically significant (P<0.05). Conclusions: DR patients express high levels of IL-6, TNF-α and VEGF, and there exists significant oxidative stress in DR, which shows that the inflammation occurrence and oxidative stress state play an important role in the development of DR.

The significance test controversy revisited the fiducial Bayesian alternative

CERN Document Server

Lecoutre, Bruno

2014-01-01

The purpose of this book is not only to revisit the “significance test controversy,”but also to provide a conceptually sounder alternative. As such, it presents a Bayesian framework for a new approach to analyzing and interpreting experimental data. It also prepares students and researchers for reporting on experimental results. Normative aspects: The main views of statistical tests are revisited and the philosophies of Fisher, Neyman-Pearson and Jeffrey are discussed in detail. Descriptive aspects: The misuses of Null Hypothesis Significance Tests are reconsidered in light of Jeffreys’ Bayesian conceptions concerning the role of statistical inference in experimental investigations. Prescriptive aspects: The current effect size and confidence interval reporting practices are presented and seriously questioned. Methodological aspects are carefully discussed and fiducial Bayesian methods are proposed as a more suitable alternative for reporting on experimental results. In closing, basic routine procedures...

The SACE Review Panel's Final Report: Significant Flaws in the Analysis of Statistical Data

Science.gov (United States)

Gregory, Kelvin

2006-01-01

The South Australian Certificate of Education (SACE) is a credential and formal qualification within the Australian Qualifications Framework. A recent review of the SACE outlined a number of recommendations for significant changes to this certificate. These recommendations were the result of a process that began with the review panel…

Evaluation of resistance of teeth subjected to fracture after endodontic treatment using different root canal sealers: An in vitro study

Directory of Open Access Journals (Sweden)

S S Bhat

2012-01-01

Full Text Available Aims: The aim of this study was to compare the ex-vivo effects of different root canal sealers on the fracture resistance of endodontically treated teeth. Materials and Methods: Seventy-five freshly extracted human mandibular premolars were used for the study. The length was standardized to 14 mm and all the teeth were biomechanically prepared and divided into five different groups based on the type of root canal sealers used. Group I:- Roeko seal + gutta percha, Group II: AH plus ® root canal sealer + gutta percha, Group III: PULPDENT root canal sealer + gutta percha, Group IV: Zinc oxide-eugenol sealer + gutta percha, Group V: Control (unobturated teeth. The teeth were embedded in acrylic resin blocks and compressive strengths were measured using universal testing machine (Instron. Statistical Analysis Used: One-way ANOVA, unpaired t- test Results: Data obtained were statistically evaluated using one-way ANOVA and unpaired t-test. All groups showed a statistically significant result (P < 0.05. Teeth obturated with Group I and Group II showed higher resistance to fracture than teeth obturated with other three Groups. It was seen that the teeth obturated with group III showed a better fracture resistance than Group IV and there was no statistical significance found between Group and Group V. Conclusions: From this study, it has been concluded that both the resin based sealers that were used in this study were equally effective compared to that of the zinc oxide-based sealers and the control group. However, no significant results were obtained when the comparison was made between zinc oxide-eugenol and gutta-percha and the control group.

Usage Statistics

Science.gov (United States)

... this page: https://medlineplus.gov/usestatistics.html MedlinePlus Statistics To use the sharing features on this page, ... By Quarter View image full size Quarterly User Statistics Quarter Page Views Unique Visitors Oct-Dec-98 ...

Second Language Experience Facilitates Statistical Learning of Novel Linguistic Materials.

Science.gov (United States)

Potter, Christine E; Wang, Tianlin; Saffran, Jenny R

2017-04-01

Recent research has begun to explore individual differences in statistical learning, and how those differences may be related to other cognitive abilities, particularly their effects on language learning. In this research, we explored a different type of relationship between language learning and statistical learning: the possibility that learning a new language may also influence statistical learning by changing the regularities to which learners are sensitive. We tested two groups of participants, Mandarin Learners and Naïve Controls, at two time points, 6 months apart. At each time point, participants performed two different statistical learning tasks: an artificial tonal language statistical learning task and a visual statistical learning task. Only the Mandarin-learning group showed significant improvement on the linguistic task, whereas both groups improved equally on the visual task. These results support the view that there are multiple influences on statistical learning. Domain-relevant experiences may affect the regularities that learners can discover when presented with novel stimuli. Copyright © 2016 Cognitive Science Society, Inc.

Empirical and Statistical Evaluation of the Effectiveness of Four Lossless Data Compression Algorithms

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N. A. Azeez

2017-04-01

Full Text Available Data compression is the process of reducing the size of a file to effectively reduce storage space and communication cost. The evolvement in technology and digital age has led to an unparalleled usage of digital files in this current decade. The usage of data has resulted to an increase in the amount of data being transmitted via various channels of data communication which has prompted the need to look into the current lossless data compression algorithms to check for their level of effectiveness so as to maximally reduce the bandwidth requirement in communication and transfer of data. Four lossless data compression algorithm: Lempel-Ziv Welch algorithm, Shannon-Fano algorithm, Adaptive Huffman algorithm and Run-Length encoding have been selected for implementation. The choice of these algorithms was based on their similarities, particularly in application areas. Their level of efficiency and effectiveness were evaluated using some set of predefined performance evaluation metrics namely compression ratio, compression factor, compression time, saving percentage, entropy and code efficiency. The algorithms implementation was done in the NetBeans Integrated Development Environment using Java as the programming language. Through the statistical analysis performed using Boxplot and ANOVA and comparison made on the four algo

Optimization of Ficus deltoidea Using Ultrasound-Assisted Extraction by Box-Behnken Statistical Design

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L. J. Ong

2016-09-01

Full Text Available In this study, the effect of extraction parameters (ethanol concentration, sonication time, and solvent-to-sample ratio on Ficus deltoidea leaves was investigated using ultrasound-assisted extraction by response surface methodology (RSM. Total phenolic content (TPC of F. deltoidea extracts was identified using Folin-Ciocalteu method and expressed in gallic acid equivalent (GAE per g. Box-Behnken statistical design (BBD was the tool used to find the optimal conditions for maximum TPC. Besides, the extraction yield was measured and stated in percentage. The optimized TPC attained was 455.78 mg GAE/g at 64% ethanol concentration, 10 minutes sonication time, and 20 mL/g solvent-to-sample ratio whereas the greatest extraction yield was 33% with ethanol concentration of 70%, sonication time of 40 minutes, and solvent-to-material ratio at 40 mL/g. The determination coefficient, R2, for TPC indicates that 99.5% capriciousness in the response could be clarified by the ANOVA model and the value of 0.9681 of predicted R2 is in equitable agreement with the 0.9890 of adjusted R2. The present study shows that ethanol water as solvent, a short time of 10 minutes, and adequate solvent-to-sample ratio (20 mL/g are the best conditions for extraction.

Measuring radioactive half-lives via statistical sampling in practice

Science.gov (United States)

Lorusso, G.; Collins, S. M.; Jagan, K.; Hitt, G. W.; Sadek, A. M.; Aitken-Smith, P. M.; Bridi, D.; Keightley, J. D.

2017-10-01

The statistical sampling method for the measurement of radioactive decay half-lives exhibits intriguing features such as that the half-life is approximately the median of a distribution closely resembling a Cauchy distribution. Whilst initial theoretical considerations suggested that in certain cases the method could have significant advantages, accurate measurements by statistical sampling have proven difficult, for they require an exercise in non-standard statistical analysis. As a consequence, no half-life measurement using this method has yet been reported and no comparison with traditional methods has ever been made. We used a Monte Carlo approach to address these analysis difficulties, and present the first experimental measurement of a radioisotope half-life (211Pb) by statistical sampling in good agreement with the literature recommended value. Our work also focused on the comparison between statistical sampling and exponential regression analysis, and concluded that exponential regression achieves generally the highest accuracy.

Semiconductor statistics

CERN Document Server

Blakemore, J S

1962-01-01

Semiconductor Statistics presents statistics aimed at complementing existing books on the relationships between carrier densities and transport effects. The book is divided into two parts. Part I provides introductory material on the electron theory of solids, and then discusses carrier statistics for semiconductors in thermal equilibrium. Of course a solid cannot be in true thermodynamic equilibrium if any electrical current is passed; but when currents are reasonably small the distribution function is but little perturbed, and the carrier distribution for such a """"quasi-equilibrium"""" co

Statistical analogues of thermodynamic extremum principles

Science.gov (United States)

Ramshaw, John D.

2018-05-01

As shown by Jaynes, the canonical and grand canonical probability distributions of equilibrium statistical mechanics can be simply derived from the principle of maximum entropy, in which the statistical entropy S=- {k}{{B}}{\\sum }i{p}i{log}{p}i is maximised subject to constraints on the mean values of the energy E and/or number of particles N in a system of fixed volume V. The Lagrange multipliers associated with those constraints are then found to be simply related to the temperature T and chemical potential μ. Here we show that the constrained maximisation of S is equivalent to, and can therefore be replaced by, the essentially unconstrained minimisation of the obvious statistical analogues of the Helmholtz free energy F = E ‑ TS and the grand potential J = F ‑ μN. Those minimisations are more easily performed than the maximisation of S because they formally eliminate the constraints on the mean values of E and N and their associated Lagrange multipliers. This procedure significantly simplifies the derivation of the canonical and grand canonical probability distributions, and shows that the well known extremum principles for the various thermodynamic potentials possess natural statistical analogues which are equivalent to the constrained maximisation of S.

Statistics without Tears: Complex Statistics with Simple Arithmetic

Science.gov (United States)

Smith, Brian

2011-01-01

One of the often overlooked aspects of modern statistics is the analysis of time series data. Modern introductory statistics courses tend to rush to probabilistic applications involving risk and confidence. Rarely does the first level course linger on such useful and fascinating topics as time series decomposition, with its practical applications…

Stochastic simulations for the time evolution of systems which obey generalized statistics: fractional exclusion statistics and Gentile's statistics

International Nuclear Information System (INIS)

Nemnes, G A; Anghel, D V

2010-01-01

We present a stochastic method for the simulation of the time evolution in systems which obey generalized statistics, namely fractional exclusion statistics and Gentile's statistics. The transition rates are derived in the framework of canonical ensembles. This approach introduces a tool for describing interacting fermionic and bosonic systems in non-equilibrium as ideal FES systems, in a computationally efficient manner. The two types of statistics are analyzed comparatively, indicating their intrinsic thermodynamic differences and revealing key aspects related to the species size

Sibling Competition & Growth Tradeoffs. Biological vs. Statistical Significance

OpenAIRE

Kramer, Karen L.; Veile, Amanda; Ot?rola-Castillo, Erik

2016-01-01

Early childhood growth has many downstream effects on future health and reproduction and is an important measure of offspring quality. While a tradeoff between family size and child growth outcomes is theoretically predicted in high-fertility societies, empirical evidence is mixed. This is often attributed to phenotypic variation in parental condition. However, inconsistent study results may also arise because family size confounds the potentially differential effects that older and younger s...

Principles of Statistics: What the Sports Medicine Professional Needs to Know.

Science.gov (United States)

Riemann, Bryan L; Lininger, Monica R

2018-07-01

Understanding the results and statistics reported in original research remains a large challenge for many sports medicine practitioners and, in turn, may be among one of the biggest barriers to integrating research into sports medicine practice. The purpose of this article is to provide minimal essentials a sports medicine practitioner needs to know about interpreting statistics and research results to facilitate the incorporation of the latest evidence into practice. Topics covered include the difference between statistical significance and clinical meaningfulness; effect sizes and confidence intervals; reliability statistics, including the minimal detectable difference and minimal important difference; and statistical power. Copyright © 2018 Elsevier Inc. All rights reserved.

Cut points for identifying clinically significant diabetes distress in adolescents with type 1 diabetes using the PAID-T

DEFF Research Database (Denmark)

Hagger, Virginia; Hendrieckx, Christel; Cameron, Fergus

2017-01-01

OBJECTIVE To establish cut point(s) for the Problem Areas in Diabetes-teen version (PAID-T) scale to identify adolescents with clinically meaningful, elevated diabetes distress. RESEARCH DESIGN AND METHODS Data were available from the Diabetes Management and Impact for Long-term Empowerment...... variables were examined to identify a clinically meaningful threshold for elevated diabetes distress. ANOVA was used to test whether these variables differed by levels of distress. RESULTS Two cut points distinguished none-to-mild (90) diabetes distress.......Moderate distresswas experienced by 18%of adolescents and high distress by 36%. Mean depressive symptoms, self-reported HbA1c, and SMBG differed significantly across the three levels of diabetes distress (all P defined two...

Reversible Statistics

DEFF Research Database (Denmark)

Tryggestad, Kjell

2004-01-01

The study aims is to describe how the inclusion and exclusion of materials and calculative devices construct the boundaries and distinctions between statistical facts and artifacts in economics. My methodological approach is inspired by John Graunt's (1667) Political arithmetic and more recent work...... within constructivism and the field of Science and Technology Studies (STS). The result of this approach is here termed reversible statistics, reconstructing the findings of a statistical study within economics in three different ways. It is argued that all three accounts are quite normal, albeit...... in different ways. The presence and absence of diverse materials, both natural and political, is what distinguishes them from each other. Arguments are presented for a more symmetric relation between the scientific statistical text and the reader. I will argue that a more symmetric relation can be achieved...

Statistical Physics

CERN Document Server

Wannier, Gregory Hugh

1966-01-01

Until recently, the field of statistical physics was traditionally taught as three separate subjects: thermodynamics, statistical mechanics, and kinetic theory. This text, a forerunner in its field and now a classic, was the first to recognize the outdated reasons for their separation and to combine the essentials of the three subjects into one unified presentation of thermal physics. It has been widely adopted in graduate and advanced undergraduate courses, and is recommended throughout the field as an indispensable aid to the independent study and research of statistical physics.Designed for

Land Use Land Cover Changes in Detection of Water Quality: A Study Based on Remote Sensing and Multivariate Statistics

Directory of Open Access Journals (Sweden)

Ang Kean Hua

2017-01-01

Full Text Available Malacca River water quality is affected due to rapid urbanization development. The present study applied LULC changes towards water quality detection in Malacca River. The method uses LULC, PCA, CCA, HCA, NHCA, and ANOVA. PCA confirmed DS, EC, salinity, turbidity, TSS, DO, BOD, COD, As, Hg, Zn, Fe, E. coli, and total coliform. CCA confirmed 14 variables into two variates; first variate involves residential and industrial activities; and second variate involves agriculture, sewage treatment plant, and animal husbandry. HCA and NHCA emphasize that cluster 1 occurs in urban area with Hg, Fe, total coliform, and DO pollution; cluster 3 occurs in suburban area with salinity, EC, and DS; and cluster 2 occurs in rural area with salinity and EC. ANOVA between LULC and water quality data indicates that built-up area significantly polluted the water quality through E. coli, total coliform, EC, BOD, COD, TSS, Hg, Zn, and Fe, while agriculture activities cause EC, TSS, salinity, E. coli, total coliform, arsenic, and iron pollution; and open space causes contamination of turbidity, salinity, EC, and TSS. Research finding provided useful information in identifying pollution sources and understanding LULC with river water quality as references to policy maker for proper management of Land Use area.

SPECT versus planar bone radionuclide imaging in the detection of spondylolysis

International Nuclear Information System (INIS)

Whitten, C.G.; El-Khoury, G.Y.; Chang, P.J.; Seabold, J.E.; Found, E.M.; Renfrew, D.L.

1991-01-01

This paper evaluates the relative performance and ease of interpretation of SPECT versus planar radionuclide bone imaging in the detection of spondylolysis. The authors studied all patients presenting with back pain suggestive of spondylolysis from November 1989 to January 1991 who underwent bone scanning; patients underwent both planar and SPECT imaging. The planar and SPECT images were randomly mixed and independently interpreted by four observers for presence or absence of spondylolysis and ease of interpretation for each scan. Receiver operating characteristic (ROC) and analysis of variance (ANOVA) were used. Of 72 patients, 19 had confirmed spondylolysis, and 53 did not. While ROC analysis showed that SPECT performed slightly better than planar imaging for all four observers, the difference was not statistically significant. ANOVA results suggest that planar imaging was significantly easier to use than SPECT and that ease of use was strongly correlated with the observer's confidence in the diagnosis

SU-F-T-386: Analysis of Three QA Methods for Predicting Dose Deviation Pass Percentage for Lung SBRT VMAT Plans

Energy Technology Data Exchange (ETDEWEB)

Hardin, M; To, D; Giaddui, T; Li, J; Yu, Y; Harrison, A [Thomas Jefferson University, Philadelphia, PA (United States)

2016-06-15

Purpose: To investigate the significance of using pinpoint ionization chambers (IC) and RadCalc (RC) in determining the quality of lung SBRT VMAT plans with low dose deviation pass percentage (DDPP) as reported by ScandiDos Delta4 (D4). To quantify the relationship between DDPP and point dose deviations determined by IC (ICDD), RadCalc (RCDD), and median dose deviation reported by D4 (D4DD). Methods: Point dose deviations and D4 DDPP were compiled for 45 SBRT VMAT plans. Eighteen patients were treated on Varian Truebeam linear accelerators (linacs); the remaining 27 were treated on Elekta Synergy linacs with Agility collimators. A one-way analysis of variance (ANOVA) was performed to determine if there were any statistically significant differences between D4DD, ICDD, and RCDD. Tukey’s test was used to determine which pair of means was statistically different from each other. Multiple regression analysis was performed to determine if D4DD, ICDD, or RCDD are statistically significant predictors of DDPP. Results: Median DDPP, D4DD, ICDD, and RCDD were 80.5% (47.6%–99.2%), −0.3% (−2.0%–1.6%), 0.2% (−7.5%–6.3%), and 2.9% (−4.0%–19.7%), respectively. The ANOVA showed a statistically significant difference between D4DD, ICDD, and RCDD for a 95% confidence interval (p < 0.001). Tukey’s test revealed a statistically significant difference between two pairs of groups, RCDD-D4DD and RCDD-ICDD (p < 0.001), but no difference between ICDD-D4DD (p = 0.485). Multiple regression analysis revealed that ICDD (p = 0.04) and D4DD (p = 0.03) are statistically significant predictors of DDPP with an adjusted r{sup 2} of 0.115. Conclusion: This study shows ICDD predicts trends in D4 DDPP; however this trend is highly variable as shown by our low r{sup 2}. This work suggests that ICDD can be used as a method to verify DDPP in delivery of lung SBRT VMAT plans. RCDD may not validate low DDPP discovered in D4 QA for small field SBRT treatments.

Managing Macroeconomic Risks by Using Statistical Simulation

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Merkaš Zvonko

2017-06-01

Full Text Available The paper analyzes the possibilities of using statistical simulation in the macroeconomic risks measurement. At the level of the whole world, macroeconomic risks are, due to the excessive imbalance, significantly increased. Using analytical statistical methods and Monte Carlo simulation, the authors interpret the collected data sets, compare and analyze them in order to mitigate potential risks. The empirical part of the study is a qualitative case study that uses statistical methods and Monte Carlo simulation for managing macroeconomic risks, which is the central theme of this work. Application of statistical simulation is necessary because the system, for which it is necessary to specify the model, is too complex for an analytical approach. The objective of the paper is to point out the previous need for consideration of significant macroeconomic risks, particularly in terms of the number of the unemployed in the society, the movement of gross domestic product and the country’s credit rating, and the use of data previously processed by statistical methods, through statistical simulation, to analyze the existing model of managing the macroeconomic risks and suggest elements for a management model development that will allow, with the lowest possible probability and consequences, the emergence of the recent macroeconomic risks. The stochastic characteristics of the system, defined by random variables as input values defined by probability distributions, require the performance of a large number of iterations on which to record the output of the model and calculate the mathematical expectations. The paper expounds the basic procedures and techniques of discrete statistical simulation applied to systems that can be characterized by a number of events which represent a set of circumstances that have caused a change in the system’s state and the possibility of its application in the field of assessment of macroeconomic risks. The method has no

Attitudes toward statistics in medical postgraduates: measuring, evaluating and monitoring.

Science.gov (United States)

Zhang, Yuhai; Shang, Lei; Wang, Rui; Zhao, Qinbo; Li, Chanjuan; Xu, Yongyong; Su, Haixia

2012-11-23

In medical training, statistics is considered a very difficult course to learn and teach. Current studies have found that students' attitudes toward statistics can influence their learning process. Measuring, evaluating and monitoring the changes of students' attitudes toward statistics are important. Few studies have focused on the attitudes of postgraduates, especially medical postgraduates. Our purpose was to understand current attitudes regarding statistics held by medical postgraduates and explore their effects on students' achievement. We also wanted to explore the influencing factors and the sources of these attitudes and monitor their changes after a systematic statistics course. A total of 539 medical postgraduates enrolled in a systematic statistics course completed the pre-form of the Survey of Attitudes Toward Statistics -28 scale, and 83 postgraduates were selected randomly from among them to complete the post-form scale after the course. Most medical postgraduates held positive attitudes toward statistics, but they thought statistics was a very difficult subject. The attitudes mainly came from experiences in a former statistical or mathematical class. Age, level of statistical education, research experience, specialty and mathematics basis may influence postgraduate attitudes toward statistics. There were significant positive correlations between course achievement and attitudes toward statistics. In general, student attitudes showed negative changes after completing a statistics course. The importance of student attitudes toward statistics must be recognized in medical postgraduate training. To make sure all students have a positive learning environment, statistics teachers should measure their students' attitudes and monitor their change of status during a course. Some necessary assistance should be offered for those students who develop negative attitudes.

IDENTIFICATION OF THOSE VARIABLES THAT HAVE A SIGNIFICANT INFLUENCE ON THE EXPECTED NUMBER OF DAYS OF STAYING IN THE CENTRE DEVELOPMENT REGION OF ROMANIA

Directory of Open Access Journals (Sweden)

Erika KULCSÁR

2010-06-01

Full Text Available I started from the assumption that there are more variables that have a significant influence on the expected number of days of staying in the Centre Development Region. To identify those variables this paper includes the analysis of variance with two variables that are not interacting, in this case the dependent variable is the question "How many days did you plan to stay in Centre Development Region?" and the independent variables are: "What is the purpose of your stay?" "What is the highest level of education?". Given that there are cases when interactions occur between variables, I also analyzed the interaction effects between the two independent variables. The paper also includes an ANOVA analysis with three variables between which interactions relationships occur. After identifying the dependency relations between the variables I found that the inclusion of the third variable, namely the "Marital status" of respondents, adds value to the model. Following the results obtained by ANOVA analysis, I identified those socio-demographic characteristics that, in my opinion, companies that operate on tourist market in the Center Development Region should consider when fundamenting marketing strategies in tourism.

ONE WAY ANOVA RANDOMIZED COMPLETE BLOCKS

African Journals Online (AJOL)

******

2012-04-24

Apr 24, 2012 ... Key words: Grey mullet, growth, foreign DNA, genetically modified. INTRODUCTION ... ration, food quality and preservation (Shears et al., 1991;. Chen et al. ... fish eggs (Khoo et al., 1992) and 4) direct injection of foreign DNA ...

An Analytic Solution to the Computation of Power and Sample Size for Genetic Association Studies under a Pleiotropic Mode of Inheritance.

Science.gov (United States)

Gordon, Derek; Londono, Douglas; Patel, Payal; Kim, Wonkuk; Finch, Stephen J; Heiman, Gary A

2016-01-01

Our motivation here is to calculate the power of 3 statistical tests used when there are genetic traits that operate under a pleiotropic mode of inheritance and when qualitative phenotypes are defined by use of thresholds for the multiple quantitative phenotypes. Specifically, we formulate a multivariate function that provides the probability that an individual has a vector of specific quantitative trait values conditional on having a risk locus genotype, and we apply thresholds to define qualitative phenotypes (affected, unaffected) and compute penetrances and conditional genotype frequencies based on the multivariate function. We extend the analytic power and minimum-sample-size-necessary (MSSN) formulas for 2 categorical data-based tests (genotype, linear trend test [LTT]) of genetic association to the pleiotropic model. We further compare the MSSN of the genotype test and the LTT with that of a multivariate ANOVA (Pillai). We approximate the MSSN for statistics by linear models using a factorial design and ANOVA. With ANOVA decomposition, we determine which factors most significantly change the power/MSSN for all statistics. Finally, we determine which test statistics have the smallest MSSN. In this work, MSSN calculations are for 2 traits (bivariate distributions) only (for illustrative purposes). We note that the calculations may be extended to address any number of traits. Our key findings are that the genotype test usually has lower MSSN requirements than the LTT. More inclusive thresholds (top/bottom 25% vs. top/bottom 10%) have higher sample size requirements. The Pillai test has a much larger MSSN than both the genotype test and the LTT, as a result of sample selection. With these formulas, researchers can specify how many subjects they must collect to localize genes for pleiotropic phenotypes. © 2017 S. Karger AG, Basel.

phosphorus sorption capacity as a guide for phosphorus availability

African Journals Online (AJOL)

Prof. Adipala Ekwamu

drained, light yellowish brown, loamy sand ... Dongola 2 Akked series: Deep, dark grayish brown, clay ... energy. Statistical analysis. Data collected were statistically analysed using ANOVA of MStatc ... phosphorus sorbed versus phosphorus.

Estimating heat-to-heat variation in mechanical properties from a statistician's point of view

International Nuclear Information System (INIS)

Hebble, T.L.

1976-01-01

A statistical technique known as analysis of variance (ANOVA) is used to estimate the variance and standard deviation of differences among heats. The total variation of a collection of observations and how an ANOVA can be used to partition the total variation into its sources are discussed. Then, the ANOVA is adapted to published Japanese data indicating how to estimate heat-to-heat variation. Finally, numerical results are computed for several tensile and creep properties of Types 304 and 316 SS

Breakthroughs in statistics

CERN Document Server

Johnson, Norman

This is author-approved bcc: This is the third volume of a collection of seminal papers in the statistical sciences written during the past 110 years. These papers have each had an outstanding influence on the development of statistical theory and practice over the last century. Each paper is preceded by an introduction written by an authority in the field providing background information and assessing its influence. Volume III concerntrates on articles from the 1980's while including some earlier articles not included in Volume I and II. Samuel Kotz is Professor of Statistics in the College of Business and Management at the University of Maryland. Norman L. Johnson is Professor Emeritus of Statistics at the University of North Carolina. Also available: Breakthroughs in Statistics Volume I: Foundations and Basic Theory Samuel Kotz and Norman L. Johnson, Editors 1993. 631 pp. Softcover. ISBN 0-387-94037-5 Breakthroughs in Statistics Volume II: Methodology and Distribution Samuel Kotz and Norman L. Johnson, Edi...

Biostatistics Series Module 3: Comparing Groups: Numerical Variables.

Science.gov (United States)

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Numerical data that are normally distributed can be analyzed with parametric tests, that is, tests which are based on the parameters that define a normal distribution curve. If the distribution is uncertain, the data can be plotted as a normal probability plot and visually inspected, or tested for normality using one of a number of goodness of fit tests, such as the Kolmogorov-Smirnov test. The widely used Student's t-test has three variants. The one-sample t-test is used to assess if a sample mean (as an estimate of the population mean) differs significantly from a given population mean. The means of two independent samples may be compared for a statistically significant difference by the unpaired or independent samples t-test. If the data sets are related in some way, their means may be compared by the paired or dependent samples t-test. The t-test should not be used to compare the means of more than two groups. Although it is possible to compare groups in pairs, when there are more than two groups, this will increase the probability of a Type I error. The one-way analysis of variance (ANOVA) is employed to compare the means of three or more independent data sets that are normally distributed. Multiple measurements from the same set of subjects cannot be treated as separate, unrelated data sets. Comparison of means in such a situation requires repeated measures ANOVA. It is to be noted that while a multiple group comparison test such as ANOVA can point to a significant difference, it does not identify exactly between which two groups the difference lies. To do this, multiple group comparison needs to be followed up by an appropriate post hoc test. An example is the Tukey's honestly significant difference test following ANOVA. If the assumptions for parametric tests are not met, there are nonparametric alternatives for comparing data sets. These include Mann-Whitney U-test as the nonparametric counterpart of the unpaired Student's t-test, Wilcoxon signed-rank test

Vibration analysis on driver’s seat of agricultural tractors during tillage tests

International Nuclear Information System (INIS)

Gialamas, T.; Gravalos, I.; Kateris, D.; Xyradakis, P.; Dimitriadis, C.

2016-01-01

The vibration of the driver’s seat of agricultural tractors was investigated during three alternative tillage operations. Three tractors including a range of specifications were considered, at a range of forward speeds. The interactions between the tractors, implements and speeds were examined using the SPSS program and the GLM-ANOVA method. The results analysis indicated that the tractors played the first major role in vibration development in the lateral axis and was followed by the implements. In contrast, the implements played the first major role in the development of vibration in the horizontal axis and are followed by factor tractors. The statistically significant effect in vertical and horizontal axes shows the factor implements. In addition, the statistically significant effect in the vertical and lateral axes shows again the implements to be the most significant factor. Of the implements, the plough shows the highest vibration and displays statistically significant difference in comparison with the other implements.

Vibration analysis on driver’s seat of agricultural tractors during tillage tests

Energy Technology Data Exchange (ETDEWEB)

Gialamas, T.; Gravalos, I.; Kateris, D.; Xyradakis, P.; Dimitriadis, C.

2016-07-01

The vibration of the driver’s seat of agricultural tractors was investigated during three alternative tillage operations. Three tractors including a range of specifications were considered, at a range of forward speeds. The interactions between the tractors, implements and speeds were examined using the SPSS program and the GLM-ANOVA method. The results analysis indicated that the tractors played the first major role in vibration development in the lateral axis and was followed by the implements. In contrast, the implements played the first major role in the development of vibration in the horizontal axis and are followed by factor tractors. The statistically significant effect in vertical and horizontal axes shows the factor implements. In addition, the statistically significant effect in the vertical and lateral axes shows again the implements to be the most significant factor. Of the implements, the plough shows the highest vibration and displays statistically significant difference in comparison with the other implements.

The significance of reporting to the thousandths place: Figuring out the laboratory limitations

Directory of Open Access Journals (Sweden)

Joely A. Straseski

2017-04-01

Full Text Available Objectives: A request to report laboratory values to a specific number of decimal places represents a delicate balance between clinical interpretation of a true analytical change versus laboratory understanding of analytical imprecision and significant figures. Prostate specific antigen (PSA was used as an example to determine if an immunoassay routinely reported to the hundredths decimal place based on significant figure assessment in our laboratory was capable of providing analytically meaningful results when reported to the thousandths places when requested by clinicians. Design and methods: Results of imprecision studies of a representative PSA assay (Roche MODULAR E170 employing two methods of statistical analysis are reported. Sample pools were generated with target values of 0.01 and 0.20 μg/L PSA as determined by the E170. Intra-assay imprecision studies were conducted and the resultant data were analyzed using two independent statistical methods to evaluate reporting limits. Results: These statistical methods indicated reporting results to the thousandths place at the two assessed concentrations was an appropriate reflection of the measurement imprecision for the representative assay. This approach used two independent statistical tests to determine the ability of an analytical system to support a desired reporting level. Importantly, data were generated during a routine intra-assay imprecision study, thus this approach does not require extra data collection by the laboratory. Conclusions: Independent statistical analysis must be used to determine appropriate significant figure limitations for clinically relevant analytes. Establishing these limits is the responsibility of the laboratory and should be determined prior to providing clinical results. Keywords: Significant figures, Imprecision, Prostate cancer, Prostate specific antigen, PSA

The new statistics: why and how.

Science.gov (United States)

Cumming, Geoff

2014-01-01

We need to make substantial changes to how we conduct research. First, in response to heightened concern that our published research literature is incomplete and untrustworthy, we need new requirements to ensure research integrity. These include prespecification of studies whenever possible, avoidance of selection and other inappropriate data-analytic practices, complete reporting, and encouragement of replication. Second, in response to renewed recognition of the severe flaws of null-hypothesis significance testing (NHST), we need to shift from reliance on NHST to estimation and other preferred techniques. The new statistics refers to recommended practices, including estimation based on effect sizes, confidence intervals, and meta-analysis. The techniques are not new, but adopting them widely would be new for many researchers, as well as highly beneficial. This article explains why the new statistics are important and offers guidance for their use. It describes an eight-step new-statistics strategy for research with integrity, which starts with formulation of research questions in estimation terms, has no place for NHST, and is aimed at building a cumulative quantitative discipline.

Potential errors and misuse of statistics in studies on leakage in endodontics.

Science.gov (United States)

Lucena, C; Lopez, J M; Pulgar, R; Abalos, C; Valderrama, M J

2013-04-01

To assess the quality of the statistical methodology used in studies of leakage in Endodontics, and to compare the results found using appropriate versus inappropriate inferential statistical methods. The search strategy used the descriptors 'root filling' 'microleakage', 'dye penetration', 'dye leakage', 'polymicrobial leakage' and 'fluid filtration' for the time interval 2001-2010 in journals within the categories 'Dentistry, Oral Surgery and Medicine' and 'Materials Science, Biomaterials' of the Journal Citation Report. All retrieved articles were reviewed to find potential pitfalls in statistical methodology that may be encountered during study design, data management or data analysis. The database included 209 papers. In all the studies reviewed, the statistical methods used were appropriate for the category attributed to the outcome variable, but in 41% of the cases, the chi-square test or parametric methods were inappropriately selected subsequently. In 2% of the papers, no statistical test was used. In 99% of cases, a statistically 'significant' or 'not significant' effect was reported as a main finding, whilst only 1% also presented an estimation of the magnitude of the effect. When the appropriate statistical methods were applied in the studies with originally inappropriate data analysis, the conclusions changed in 19% of the cases. Statistical deficiencies in leakage studies may affect their results and interpretation and might be one of the reasons for the poor agreement amongst the reported findings. Therefore, more effort should be made to standardize statistical methodology. © 2012 International Endodontic Journal.

Optimizing Injection Molding Parameters of Different Halloysites Type-Reinforced Thermoplastic Polyurethane Nanocomposites via Taguchi Complemented with ANOVA

Directory of Open Access Journals (Sweden)

Tayser Sumer Gaaz

2016-11-01

Taguchi and ANOVA approaches. Seemingly, mHNTs has shown its very important role in the resulting product.

Statistical density of nuclear excited states

Directory of Open Access Journals (Sweden)

V. M. Kolomietz

2015-10-01

Full Text Available A semi-classical approximation is applied to the calculations of single-particle and statistical level densities in excited nuclei. Landau's conception of quasi-particles with the nucleon effective mass m* < m is used. The approach provides the correct description of the continuum contribution to the level density for realistic finite-depth potentials. It is shown that the continuum states does not affect significantly the thermodynamic calculations for sufficiently small temperatures T ≤ 1 MeV but reduce strongly the results for the excitation energy at high temperatures. By use of standard Woods - Saxon potential and nucleon effective mass m* = 0.7m the A-dependency of the statistical level density parameter K was evaluated in a good qualitative agreement with experimental data.

Statistical monitoring of linear antenna arrays

KAUST Repository

Harrou, Fouzi

2016-11-03

The paper concerns the problem of monitoring linear antenna arrays using the generalized likelihood ratio (GLR) test. When an abnormal event (fault) affects an array of antenna elements, the radiation pattern changes and significant deviation from the desired design performance specifications can resulted. In this paper, the detection of faults is addressed from a statistical point of view as a fault detection problem. Specifically, a statistical method rested on the GLR principle is used to detect potential faults in linear arrays. To assess the strength of the GLR-based monitoring scheme, three case studies involving different types of faults were performed. Simulation results clearly shown the effectiveness of the GLR-based fault-detection method to monitor the performance of linear antenna arrays.

Paradigms and pragmatism: approaches to medical statistics.

Science.gov (United States)

Healy, M J

2000-01-01

Until recently, the dominant philosophy of science was that due to Karl Popper, with its doctrine that the proper task of science was the formulation of hypotheses followed by attempts at refuting them. In spite of the close analogy with significance testing, these ideas do not fit well with the practice of medical statistics. The same can be said of the later philosophy of Thomas Kuhn, who maintains that science proceeds by way of revolutionary upheavals separated by periods of relatively pedestrian research which are governed by what Kuhn refers to as paradigms. Through there have been paradigm shifts in the history of statistics, a degree of continuity can also be discerned. A current paradigm shift is embodied in the spread of Bayesian ideas. It may be that a future paradigm will emphasise the pragmatic approach to statistics that is associated with the name of Daniel Schwartz.

Modelos de variación de la composición bioquímica de Mesopodopsis slabberi (Van Beneden, 1861) (Crustacea: Mysidacea)

OpenAIRE

Azeiteiro, U.M.; Fonseca, J.C.; Pastorinho, R.; Morgado, F.; Marques, J. C.

2003-01-01

In order to assess the patterns of variation in the biochemical composition of Mesopodopsis slabberi (Van Beneden, 1861) in a temperate estuary, we determined the protein, carbohydrate, chitin and lipid contents of freshly caught immature individuals (juveniles), adult males, and adult females during two annual cycles. Statistical analysis (anova) revealed significant differences in the biochemical components between months and development stages for the months analysed. All of the biochemica...

The Relation between Work Family Conflict and Employee Performance: A Research on Hotel Employee

OpenAIRE

KARAKAŞ, Ayhan; SAHİN, Nilufer

2017-01-01

The aim of thisstudy was, to examine the relation between work family conflict and  employeeperformance. To measure the relationship ,WFC and EP scales used. Data weregathered from hotel employees in Western Black Sea provinces. End of the study,through data were examined -obtained statistical software package-, frequencyanalysis, correlation analysis, t-test, ANOVA test and regression analysis. Theresult indicate that  work familyconflict related significantly to employee performance. Employ...

Statistical Anxiety and Attitudes Towards Statistics: Development of a Comprehensive Danish Instrument

DEFF Research Database (Denmark)

Nielsen, Tine; Kreiner, Svend

Short abstract Motivated by experiencing with students’ psychological barriers for learning statistics we modified and extended the Statistical Anxiety Rating Scale (STARS) to develop a contemporary Danish measure of attitudes and relationship to statistics for use with higher education students...... with evidence of DIF in all cases: One TCA-item functioned differentially relative to age, one WS-item functioned differentially relative to statistics course (first or second), and two IA-items functioned differentially relative to statistics course and academic discipline (sociology, public health...

Ethics in Statistics

Science.gov (United States)

Lenard, Christopher; McCarthy, Sally; Mills, Terence

2014-01-01

There are many different aspects of statistics. Statistics involves mathematics, computing, and applications to almost every field of endeavour. Each aspect provides an opportunity to spark someone's interest in the subject. In this paper we discuss some ethical aspects of statistics, and describe how an introduction to ethics has been…

Statistics

International Nuclear Information System (INIS)

1999-01-01

For the year 1998 and the year 1999, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g. Energiatilastot 1998, Statistics Finland, Helsinki 1999, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in January-June 1999, Energy exports by recipient country in January-June 1999, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products