Bias expansion of spatial statistics and approximation of differenced ...
Indian Academy of Sciences (India)
Investigations of spatial statistics, computed from lattice data in the plane, can lead to a special lattice point counting problem. The statistical goal is to expand the asymptotic expectation or large-sample bias of certain spatial covariance estimators, where this bias typically depends on the shape of a spatial sampling region.
Targeted estimation of nuisance parameters to obtain valid statistical inference.
van der Laan, Mark J
2014-01-01
In order to obtain concrete results, we focus on estimation of the treatment specific mean, controlling for all measured baseline covariates, based on observing independent and identically distributed copies of a random variable consisting of baseline covariates, a subsequently assigned binary treatment, and a final outcome. The statistical model only assumes possible restrictions on the conditional distribution of treatment, given the covariates, the so-called propensity score. Estimators of the treatment specific mean involve estimation of the propensity score and/or estimation of the conditional mean of the outcome, given the treatment and covariates. In order to make these estimators asymptotically unbiased at any data distribution in the statistical model, it is essential to use data-adaptive estimators of these nuisance parameters such as ensemble learning, and specifically super-learning. Because such estimators involve optimal trade-off of bias and variance w.r.t. the infinite dimensional nuisance parameter itself, they result in a sub-optimal bias/variance trade-off for the resulting real-valued estimator of the estimand. We demonstrate that additional targeting of the estimators of these nuisance parameters guarantees that this bias for the estimand is second order and thereby allows us to prove theorems that establish asymptotic linearity of the estimator of the treatment specific mean under regularity conditions. These insights result in novel targeted minimum loss-based estimators (TMLEs) that use ensemble learning with additional targeted bias reduction to construct estimators of the nuisance parameters. In particular, we construct collaborative TMLEs (C-TMLEs) with known influence curve allowing for statistical inference, even though these C-TMLEs involve variable selection for the propensity score based on a criterion that measures how effective the resulting fit of the propensity score is in removing bias for the estimand. As a particular special
Statistical methods for accurately determining criticality code bias
International Nuclear Information System (INIS)
Trumble, E.F.; Kimball, K.D.
1997-01-01
A system of statistically treating validation calculations for the purpose of determining computer code bias is provided in this paper. The following statistical treatments are described: weighted regression analysis, lower tolerance limit, lower tolerance band, and lower confidence band. These methods meet the criticality code validation requirements of ANS 8.1. 8 refs., 5 figs., 4 tabs
Reducing bias in the analysis of counting statistics data
International Nuclear Information System (INIS)
Hammersley, A.P.; Antoniadis, A.
1997-01-01
In the analysis of counting statistics data it is common practice to estimate the variance of the measured data points as the data points themselves. This practice introduces a bias into the results of further analysis which may be significant, and under certain circumstances lead to false conclusions. In the case of normal weighted least squares fitting this bias is quantified and methods to avoid it are proposed. (orig.)
New method for eliminating the statistical bias in highly turbulent flow measurements
International Nuclear Information System (INIS)
Nakao, S.I.; Terao, Y.; Hirata, K.I.; Kitakyushu Industrial Research Institute, Fukuoka, Japan)
1987-01-01
A simple method was developed for eliminating statistical bias which can be applied to highly turbulent flows with the sparse and nonuniform seeding conditions. Unlike the method proposed so far, a weighting function was determined based on the idea that the statistical bias could be eliminated if the asymmetric form of the probability density function of the velocity data were corrected. Moreover, the data more than three standard deviations away from the mean were discarded to remove the apparent turbulent intensity resulting from noise. The present method was applied to data obtained in the wake of a block, which provided local turbulent intensities up to about 120 percent, it was found to eliminate the statistical bias with high accuracy. 9 references
Examining publication bias—a simulation-based evaluation of statistical tests on publication bias
Directory of Open Access Journals (Sweden)
Andreas Schneck
2017-11-01
Full Text Available Background Publication bias is a form of scientific misconduct. It threatens the validity of research results and the credibility of science. Although several tests on publication bias exist, no in-depth evaluations are available that examine which test performs best for different research settings. Methods Four tests on publication bias, Egger’s test (FAT, p-uniform, the test of excess significance (TES, as well as the caliper test, were evaluated in a Monte Carlo simulation. Two different types of publication bias and its degree (0%, 50%, 100% were simulated. The type of publication bias was defined either as file-drawer, meaning the repeated analysis of new datasets, or p-hacking, meaning the inclusion of covariates in order to obtain a significant result. In addition, the underlying effect (β = 0, 0.5, 1, 1.5, effect heterogeneity, the number of observations in the simulated primary studies (N = 100, 500, and the number of observations for the publication bias tests (K = 100, 1,000 were varied. Results All tests evaluated were able to identify publication bias both in the file-drawer and p-hacking condition. The false positive rates were, with the exception of the 15%- and 20%-caliper test, unbiased. The FAT had the largest statistical power in the file-drawer conditions, whereas under p-hacking the TES was, except under effect heterogeneity, slightly better. The CTs were, however, inferior to the other tests under effect homogeneity and had a decent statistical power only in conditions with 1,000 primary studies. Discussion The FAT is recommended as a test for publication bias in standard meta-analyses with no or only small effect heterogeneity. If two-sided publication bias is suspected as well as under p-hacking the TES is the first alternative to the FAT. The 5%-caliper test is recommended under conditions of effect heterogeneity and a large number of primary studies, which may be found if publication bias is examined in a
Bias expansion of spatial statistics and approximation of differenced ...
Indian Academy of Sciences (India)
Our goal here is to describe and illustrate the general counting problem of inter- .... A great amount of literature exists in number theory and enumerative ..... series setting, similar consideration has been given to determine bias and mean ...
Obtaining Internet Flow Statistics by Volunteer-Based System
DEFF Research Database (Denmark)
Pedersen, Jens Myrup; Bujlow, Tomasz
2012-01-01
In this paper we demonstrate how the Volunteer Based System for Research on the Internet, developed at Aalborg University, can be used for creating statistics of Internet usage. Since the data is collected on individual machines, the statistics can be made on the basis of both individual users......, and average flow durations. The paper is concluded with a discussion on what further statistics can be made, and the further development of the system....
Bespoke Bias for Obtaining Free Energy Differences within Variationally Enhanced Sampling.
McCarty, James; Valsson, Omar; Parrinello, Michele
2016-05-10
Obtaining efficient sampling of multiple metastable states through molecular dynamics and hence determining free energy differences is central for understanding many important phenomena. Here we present a new biasing strategy, which employs the recent variationally enhanced sampling approach (Valsson and Parrinello Phys. Rev. Lett. 2014, 113, 090601). The bias is constructed from an intuitive model of the local free energy surface describing fluctuations around metastable minima and depends on only a few parameters which are determined variationally such that efficient sampling between states is obtained. The bias constructed in this manner largely reduces the need of finding a set of collective variables that completely spans the conformational space of interest, as they only need to be a locally valid descriptor of the system about its local minimum. We introduce the method and demonstrate its power on two representative examples.
Photiadou, C.; van den Hurk, B.J.J.M.; Delden, A. van; Weerts, A.
2016-01-01
An adapted statistical bias correction method is introduced to incorporate circulation-dependence of the model precipitation bias, and its influence on estimated discharges for the Rhine basin is analyzed for a historical period. The bias correction method is tailored to time scales relevant to
Photiadou, C.; Hurk, van den B.; Delden, van A.; Weerts, A.H.
2016-01-01
An adapted statistical bias correction method is introduced to incorporate circulation-dependence of the model precipitation bias, and its influence on estimated discharges for the Rhine basin is analyzed for a historical period. The bias correction method is tailored to time scales relevant to
Photiadou, Christiana; van den Hurk, Bart; van Delden, Aarnout; Weerts, Albrecht
2015-01-01
An adapted statistical bias correction method is introduced to incorporate circulation-dependence of the model precipitation bias, and its influence on estimated discharges for the Rhine basin is analyzed for a histori- cal period. The bias correction method is tailored to time scales relevant to
Konijn, Elly A.; van de Schoot, Rens; Winter, Sonja D.; Ferguson, Christopher J.
2015-01-01
The present paper argues that an important cause of publication bias resides in traditional frequentist statistics forcing binary decisions. An alternative approach through Bayesian statistics provides various degrees of support for any hypothesis allowing balanced decisions and proper null
Polish Phoneme Statistics Obtained On Large Set Of Written Texts
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Bartosz Ziółko
2009-01-01
Full Text Available The phonetical statistics were collected from several Polish corpora. The paper is a summaryof the data which are phoneme n-grams and some phenomena in the statistics. Triphonestatistics apply context-dependent speech units which have an important role in speech recognitionsystems and were never calculated for a large set of Polish written texts. The standardphonetic alphabet for Polish, SAMPA, and methods of providing phonetic transcriptions are described.
Statistical analysis of the potassium concentration obtained through
International Nuclear Information System (INIS)
Pereira, Joao Eduardo da Silva; Silva, Jose Luiz Silverio da; Pires, Carlos Alberto da Fonseca; Strieder, Adelir Jose
2007-01-01
The present work was developed in outcrops of Santa Maria region, southern Brazil, Rio Grande do Sul State. Statistic evaluations were applied in different rock types. The possibility to distinguish different geologic units, sedimentary and volcanic (acid and basic types) by means of the statistic analyses from the use of airborne gamma-ray spectrometry integrating potash radiation emissions data with geological and geochemistry data is discussed. This Project was carried out at 1973 by Geological Survey of Brazil/Companhia de Pesquisas de Recursos Minerais. The Camaqua Project evaluated the behavior of potash concentrations generating XYZ Geosof 1997 format, one grid, thematic map and digital thematic map files from this total area. Using these data base, the integration of statistics analyses in sedimentary formations which belong to the Depressao Central do Rio Grande do Sul and/or to volcanic rocks from Planalto da Serra Geral at the border of Parana Basin was tested. Univariate statistics model was used: the media, the standard media error, and the trust limits were estimated. The Tukey's Test was used in order to compare mean values. The results allowed to create criteria to distinguish geological formations based on their potash content. The back-calibration technique was employed to transform K radiation to percentage. Inside this context it was possible to define characteristic values from radioactive potash emissions and their trust ranges in relation to geologic formations. The potash variable when evaluated in relation to geographic Universal Transverse Mercator coordinates system showed a spatial relation following one polynomial model of second order, with one determination coefficient. The statistica 7.1 software Generalist Linear Models produced by Statistics Department of Federal University of Santa Maria/Brazil was used. (author)
Statistical Bias in Maximum Likelihood Estimators of Item Parameters.
1982-04-01
34 a> E r’r~e r ,C Ie I# ne,..,.rVi rnd Id.,flfv b1 - bindk numb.r) I; ,t-i i-cd I ’ tiie bias in the maximum likelihood ,st i- i;, ’ t iIeiIrs in...NTC, IL 60088 Psychometric Laboratory University of North Carolina I ERIC Facility-Acquisitions Davie Hall 013A 4833 Rugby Avenue Chapel Hill, NC
Correction of Selection Bias in Survey Data: Is the Statistical Cure Worse Than the Bias?
Hanley, James A
2017-04-01
In previous articles in the American Journal of Epidemiology (Am J Epidemiol. 2013;177(5):431-442) and American Journal of Public Health (Am J Public Health. 2013;103(10):1895-1901), Masters et al. reported age-specific hazard ratios for the contrasts in mortality rates between obesity categories. They corrected the observed hazard ratios for selection bias caused by what they postulated was the nonrepresentativeness of the participants in the National Health Interview Study that increased with age, obesity, and ill health. However, it is possible that their regression approach to remove the alleged bias has not produced, and in general cannot produce, sensible hazard ratio estimates. First, we must consider how many nonparticipants there might have been in each category of obesity and of age at entry and how much higher the mortality rates would have to be in nonparticipants than in participants in these same categories. What plausible set of numerical values would convert the ("biased") decreasing-with-age hazard ratios seen in the data into the ("unbiased") increasing-with-age ratios that they computed? Can these values be encapsulated in (and can sensible values be recovered from) one additional internal variable in a regression model? Second, one must examine the age pattern of the hazard ratios that have been adjusted for selection. Without the correction, the hazard ratios are attenuated with increasing age. With it, the hazard ratios at older ages are considerably higher, but those at younger ages are well below one. Third, one must test whether the regression approach suggested by Masters et al. would correct the nonrepresentativeness that increased with age and ill health that I introduced into real and hypothetical data sets. I found that the approach did not recover the hazard ratio patterns present in the unselected data sets: the corrections overshot the target at older ages and undershot it at lower ages.
Castilho, Silvia Diez; Nucci, Luciana Bertoldi; Assuino, Samanta Ramos; Hansen, Lucca Ortolan
2014-06-01
To compare the age at menarche obtained by recall method according to the time elapsed since the event, in order to verify the importance of the recall bias. Were evaluated 1,671 girls (7-18 years) at schools in Campinas-SP regarding the occurrence of menarche by the status quo method (menarche: yes or no) and the recall method (date of menarche, for those who mentioned it). The age at menarche obtained by the status quo method was calculated by logit, which considers the whole group, and the age obtained by the recall method was calculated as the average of the mentioned age at menarche. In this group, the age at menarche was obtained by the difference between the date of the event and the date of birth. Girls who reported menarche (883, 52.8%) were divided into four groups according to the time elapsed since the event. To analyze the results, we used ANOVA and logistic regression for the analysis, with a significance level of 0.05. The age at menarche calculated by logit was 12.14 y/o (95% CI 12.08 to 12.20). Mean ages obtained by recall were: for those who experienced menarche within the previous year 12.26 y/o (±1.14), between > 1-2 years before, 12.29 y (±1.22); between > 2-3 years before, 12.23 y/o (±1.27); and more than 3 years before, 11.55y/o (±1.24), p recall method was similar for girls who menstruated within the previous 3 years (and approaches the age calculated by logit); when more than 3 years have passed, the recall bias was significant.
Bias in iterative reconstruction of low-statistics PET data: benefits of a resolution model
Energy Technology Data Exchange (ETDEWEB)
Walker, M D; Asselin, M-C; Julyan, P J; Feldmann, M; Matthews, J C [School of Cancer and Enabling Sciences, Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, Manchester M20 3LJ (United Kingdom); Talbot, P S [Mental Health and Neurodegeneration Research Group, Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, Manchester M20 3LJ (United Kingdom); Jones, T, E-mail: matthew.walker@manchester.ac.uk [Academic Department of Radiation Oncology, Christie Hospital, University of Manchester, Manchester M20 4BX (United Kingdom)
2011-02-21
Iterative image reconstruction methods such as ordered-subset expectation maximization (OSEM) are widely used in PET. Reconstructions via OSEM are however reported to be biased for low-count data. We investigated this and considered the impact for dynamic PET. Patient listmode data were acquired in [{sup 11}C]DASB and [{sup 15}O]H{sub 2}O scans on the HRRT brain PET scanner. These data were subsampled to create many independent, low-count replicates. The data were reconstructed and the images from low-count data were compared to the high-count originals (from the same reconstruction method). This comparison enabled low-statistics bias to be calculated for the given reconstruction, as a function of the noise-equivalent counts (NEC). Two iterative reconstruction methods were tested, one with and one without an image-based resolution model (RM). Significant bias was observed when reconstructing data of low statistical quality, for both subsampled human and simulated data. For human data, this bias was substantially reduced by including a RM. For [{sup 11}C]DASB the low-statistics bias in the caudate head at 1.7 M NEC (approx. 30 s) was -5.5% and -13% with and without RM, respectively. We predicted biases in the binding potential of -4% and -10%. For quantification of cerebral blood flow for the whole-brain grey- or white-matter, using [{sup 15}O]H{sub 2}O and the PET autoradiographic method, a low-statistics bias of <2.5% and <4% was predicted for reconstruction with and without the RM. The use of a resolution model reduces low-statistics bias and can hence be beneficial for quantitative dynamic PET.
Statistical bias correction modelling for seasonal rainfall forecast for the case of Bali island
Lealdi, D.; Nurdiati, S.; Sopaheluwakan, A.
2018-04-01
Rainfall is an element of climate which is highly influential to the agricultural sector. Rain pattern and distribution highly determines the sustainability of agricultural activities. Therefore, information on rainfall is very useful for agriculture sector and farmers in anticipating the possibility of extreme events which often cause failures of agricultural production. This research aims to identify the biases from seasonal forecast products from ECMWF (European Centre for Medium-Range Weather Forecasts) rainfall forecast and to build a transfer function in order to correct the distribution biases as a new prediction model using quantile mapping approach. We apply this approach to the case of Bali Island, and as a result, the use of bias correction methods in correcting systematic biases from the model gives better results. The new prediction model obtained with this approach is better than ever. We found generally that during rainy season, the bias correction approach performs better than in dry season.
Symmetries, invariants and generating functions: higher-order statistics of biased tracers
Munshi, Dipak
2018-01-01
Gravitationally collapsed objects are known to be biased tracers of an underlying density contrast. Using symmetry arguments, generalised biasing schemes have recently been developed to relate the halo density contrast δh with the underlying density contrast δ, divergence of velocity θ and their higher-order derivatives. This is done by constructing invariants such as s, t, ψ,η. We show how the generating function formalism in Eulerian standard perturbation theory (SPT) can be used to show that many of the additional terms based on extended Galilean and Lifshitz symmetry actually do not make any contribution to the higher-order statistics of biased tracers. Other terms can also be drastically simplified allowing us to write the vertices associated with δh in terms of the vertices of δ and θ, the higher-order derivatives and the bias coefficients. We also compute the cumulant correlators (CCs) for two different tracer populations. These perturbative results are valid for tree-level contributions but at an arbitrary order. We also take into account the stochastic nature bias in our analysis. Extending previous results of a local polynomial model of bias, we express the one-point cumulants Script SN and their two-point counterparts, the CCs i.e. Script Cpq, of biased tracers in terms of that of their underlying density contrast counterparts. As a by-product of our calculation we also discuss the results using approximations based on Lagrangian perturbation theory (LPT).
Statistical methods for elimination of guarantee-time bias in cohort studies: a simulation study
Directory of Open Access Journals (Sweden)
In Sung Cho
2017-08-01
Full Text Available Abstract Background Aspirin has been considered to be beneficial in preventing cardiovascular diseases and cancer. Several pharmaco-epidemiology cohort studies have shown protective effects of aspirin on diseases using various statistical methods, with the Cox regression model being the most commonly used approach. However, there are some inherent limitations to the conventional Cox regression approach such as guarantee-time bias, resulting in an overestimation of the drug effect. To overcome such limitations, alternative approaches, such as the time-dependent Cox model and landmark methods have been proposed. This study aimed to compare the performance of three methods: Cox regression, time-dependent Cox model and landmark method with different landmark times in order to address the problem of guarantee-time bias. Methods Through statistical modeling and simulation studies, the performance of the above three methods were assessed in terms of type I error, bias, power, and mean squared error (MSE. In addition, the three statistical approaches were applied to a real data example from the Korean National Health Insurance Database. Effect of cumulative rosiglitazone dose on the risk of hepatocellular carcinoma was used as an example for illustration. Results In the simulated data, time-dependent Cox regression outperformed the landmark method in terms of bias and mean squared error but the type I error rates were similar. The results from real-data example showed the same patterns as the simulation findings. Conclusions While both time-dependent Cox regression model and landmark analysis are useful in resolving the problem of guarantee-time bias, time-dependent Cox regression is the most appropriate method for analyzing cumulative dose effects in pharmaco-epidemiological studies.
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.
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.
Uhlemann, C.; Feix, M.; Codis, S.; Pichon, C.; Bernardeau, F.; L'Huillier, B.; Kim, J.; Hong, S. E.; Laigle, C.; Park, C.; Shin, J.; Pogosyan, D.
2018-02-01
Starting from a very accurate model for density-in-cells statistics of dark matter based on large deviation theory, a bias model for the tracer density in spheres is formulated. It adopts a mean bias relation based on a quadratic bias model to relate the log-densities of dark matter to those of mass-weighted dark haloes in real and redshift space. The validity of the parametrized bias model is established using a parametrization-independent extraction of the bias function. This average bias model is then combined with the dark matter PDF, neglecting any scatter around it: it nevertheless yields an excellent model for densities-in-cells statistics of mass tracers that is parametrized in terms of the underlying dark matter variance and three bias parameters. The procedure is validated on measurements of both the one- and two-point statistics of subhalo densities in the state-of-the-art Horizon Run 4 simulation showing excellent agreement for measured dark matter variance and bias parameters. Finally, it is demonstrated that this formalism allows for a joint estimation of the non-linear dark matter variance and the bias parameters using solely the statistics of subhaloes. Having verified that galaxy counts in hydrodynamical simulations sampled on a scale of 10 Mpc h-1 closely resemble those of subhaloes, this work provides important steps towards making theoretical predictions for density-in-cells statistics applicable to upcoming galaxy surveys like Euclid or WFIRST.
Evaluating anemometer drift: A statistical approach to correct biases in wind speed measurement
Azorin-Molina, Cesar; Asin, Jesus; McVicar, Tim R.; Minola, Lorenzo; Lopez-Moreno, Juan I.; Vicente-Serrano, Sergio M.; Chen, Deliang
2018-05-01
Recent studies on observed wind variability have revealed a decline (termed "stilling") of near-surface wind speed during the last 30-50 years over many mid-latitude terrestrial regions, particularly in the Northern Hemisphere. The well-known impact of cup anemometer drift (i.e., wear on the bearings) on the observed weakening of wind speed has been mentioned as a potential contributor to the declining trend. However, to date, no research has quantified its contribution to stilling based on measurements, which is most likely due to lack of quantification of the ageing effect. In this study, a 3-year field experiment (2014-2016) with 10-minute paired wind speed measurements from one new and one malfunctioned (i.e., old bearings) SEAC SV5 cup anemometer which has been used by the Spanish Meteorological Agency in automatic weather stations since mid-1980s, was developed for assessing for the first time the role of anemometer drift on wind speed measurement. The results showed a statistical significant impact of anemometer drift on wind speed measurements, with the old anemometer measuring lower wind speeds than the new one. Biases show a marked temporal pattern and clear dependency on wind speed, with both weak and strong winds causing significant biases. This pioneering quantification of biases has allowed us to define two regression models that correct up to 37% of the artificial bias in wind speed due to measurement with an old anemometer.
Manzanas, R.; Lucero, A.; Weisheimer, A.; Gutiérrez, J. M.
2018-02-01
Statistical downscaling methods are popular post-processing tools which are widely used in many sectors to adapt the coarse-resolution biased outputs from global climate simulations to the regional-to-local scale typically required by users. They range from simple and pragmatic Bias Correction (BC) methods, which directly adjust the model outputs of interest (e.g. precipitation) according to the available local observations, to more complex Perfect Prognosis (PP) ones, which indirectly derive local predictions (e.g. precipitation) from appropriate upper-air large-scale model variables (predictors). Statistical downscaling methods have been extensively used and critically assessed in climate change applications; however, their advantages and limitations in seasonal forecasting are not well understood yet. In particular, a key problem in this context is whether they serve to improve the forecast quality/skill of raw model outputs beyond the adjustment of their systematic biases. In this paper we analyze this issue by applying two state-of-the-art BC and two PP methods to downscale precipitation from a multimodel seasonal hindcast in a challenging tropical region, the Philippines. To properly assess the potential added value beyond the reduction of model biases, we consider two validation scores which are not sensitive to changes in the mean (correlation and reliability categories). Our results show that, whereas BC methods maintain or worsen the skill of the raw model forecasts, PP methods can yield significant skill improvement (worsening) in cases for which the large-scale predictor variables considered are better (worse) predicted by the model than precipitation. For instance, PP methods are found to increase (decrease) model reliability in nearly 40% of the stations considered in boreal summer (autumn). Therefore, the choice of a convenient downscaling approach (either BC or PP) depends on the region and the season.
Obtaining Application-based and Content-based Internet Traffic Statistics
DEFF Research Database (Denmark)
Bujlow, Tomasz; Pedersen, Jens Myrup
2012-01-01
the Volunteer-Based System for Research on the Internet, developed at Aalborg University, is capable of providing detailed statistics of Internet usage. Since an increasing amount of HTTP traffic has been observed during the last few years, the system also supports creating statistics of different kinds of HTTP...... traffic, like audio, video, file transfers, etc. All statistics can be obtained for individual users of the system, for groups of users, or for all users altogether. This paper presents results with real data collected from a limited number of real users over six months. We demonstrate that the system can...
Modular reweighting software for statistical mechanical analysis of biased equilibrium data
Sindhikara, Daniel J.
2012-07-01
Here a simple, useful, modular approach and software suite designed for statistical reweighting and analysis of equilibrium ensembles is presented. Statistical reweighting is useful and sometimes necessary for analysis of equilibrium enhanced sampling methods, such as umbrella sampling or replica exchange, and also in experimental cases where biasing factors are explicitly known. Essentially, statistical reweighting allows extrapolation of data from one or more equilibrium ensembles to another. Here, the fundamental separable steps of statistical reweighting are broken up into modules - allowing for application to the general case and avoiding the black-box nature of some “all-inclusive” reweighting programs. Additionally, the programs included are, by-design, written with little dependencies. The compilers required are either pre-installed on most systems, or freely available for download with minimal trouble. Examples of the use of this suite applied to umbrella sampling and replica exchange molecular dynamics simulations will be shown along with advice on how to apply it in the general case. New version program summaryProgram title: Modular reweighting version 2 Catalogue identifier: AEJH_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJH_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 179 118 No. of bytes in distributed program, including test data, etc.: 8 518 178 Distribution format: tar.gz Programming language: C++, Python 2.6+, Perl 5+ Computer: Any Operating system: Any RAM: 50-500 MB Supplementary material: An updated version of the original manuscript (Comput. Phys. Commun. 182 (2011) 2227) is available Classification: 4.13 Catalogue identifier of previous version: AEJH_v1_0 Journal reference of previous version: Comput. Phys. Commun. 182 (2011) 2227 Does the new
Detecting rater bias using a person-fit statistic: a Monte Carlo simulation study.
Aubin, André-Sébastien; St-Onge, Christina; Renaud, Jean-Sébastien
2018-04-01
With the Standards voicing concern for the appropriateness of response processes, we need to explore strategies that would allow us to identify inappropriate rater response processes. Although certain statistics can be used to help detect rater bias, their use is complicated by either a lack of data about their actual power to detect rater bias or the difficulty related to their application in the context of health professions education. This exploratory study aimed to establish the worthiness of pursuing the use of l z to detect rater bias. We conducted a Monte Carlo simulation study to investigate the power of a specific detection statistic, that is: the standardized likelihood l z person-fit statistics (PFS). Our primary outcome was the detection rate of biased raters, namely: raters whom we manipulated into being either stringent (giving lower scores) or lenient (giving higher scores), using the l z statistic while controlling for the number of biased raters in a sample (6 levels) and the rate of bias per rater (6 levels). Overall, stringent raters (M = 0.84, SD = 0.23) were easier to detect than lenient raters (M = 0.31, SD = 0.28). More biased raters were easier to detect then less biased raters (60% bias: 62, SD = 0.37; 10% bias: 43, SD = 0.36). The PFS l z seems to offer an interesting potential to identify biased raters. We observed detection rates as high as 90% for stringent raters, for whom we manipulated more than half their checklist. Although we observed very interesting results, we cannot generalize these results to the use of PFS with estimated item/station parameters or real data. Such studies should be conducted to assess the feasibility of using PFS to identify rater bias.
Statistical evaluation of the data obtained from the K East Basin Sandfilter Backwash Pit samples
International Nuclear Information System (INIS)
Welsh, T.L.
1994-01-01
Samples were obtained from different locations from the K Each Sandfilter Backwash Pit to characterize the sludge material. These samples were analyzed chemically for elements, radionuclides, and residual compounds. The analytical results were statistically analyzed to determine the mean analyte content and the associated variability for each mean value
International Nuclear Information System (INIS)
Clerc, F; Njiki-Menga, G-H; Witschger, O
2013-01-01
Most of the measurement strategies that are suggested at the international level to assess workplace exposure to nanomaterials rely on devices measuring, in real time, airborne particles concentrations (according different metrics). Since none of the instruments to measure aerosols can distinguish a particle of interest to the background aerosol, the statistical analysis of time resolved data requires special attention. So far, very few approaches have been used for statistical analysis in the literature. This ranges from simple qualitative analysis of graphs to the implementation of more complex statistical models. To date, there is still no consensus on a particular approach and the current period is always looking for an appropriate and robust method. In this context, this exploratory study investigates a statistical method to analyse time resolved data based on a Bayesian probabilistic approach. To investigate and illustrate the use of the this statistical method, particle number concentration data from a workplace study that investigated the potential for exposure via inhalation from cleanout operations by sandpapering of a reactor producing nanocomposite thin films have been used. In this workplace study, the background issue has been addressed through the near-field and far-field approaches and several size integrated and time resolved devices have been used. The analysis of the results presented here focuses only on data obtained with two handheld condensation particle counters. While one was measuring at the source of the released particles, the other one was measuring in parallel far-field. The Bayesian probabilistic approach allows a probabilistic modelling of data series, and the observed task is modelled in the form of probability distributions. The probability distributions issuing from time resolved data obtained at the source can be compared with the probability distributions issuing from the time resolved data obtained far-field, leading in a
Obtaining Streamflow Statistics for Massachusetts Streams on the World Wide Web
Ries, Kernell G.; Steeves, Peter A.; Freeman, Aleda; Singh, Raj
2000-01-01
A World Wide Web application has been developed to make it easy to obtain streamflow statistics for user-selected locations on Massachusetts streams. The Web application, named STREAMSTATS (available at http://water.usgs.gov/osw/streamstats/massachusetts.html ), can provide peak-flow frequency, low-flow frequency, and flow-duration statistics for most streams in Massachusetts. These statistics describe the magnitude (how much), frequency (how often), and duration (how long) of flow in a stream. The U.S. Geological Survey (USGS) has published streamflow statistics, such as the 100-year peak flow, the 7-day, 10-year low flow, and flow-duration statistics, for its data-collection stations in numerous reports. Federal, State, and local agencies need these statistics to plan and manage use of water resources and to regulate activities in and around streams. Engineering and environmental consulting firms, utilities, industry, and others use the statistics to design and operate water-supply systems, hydropower facilities, industrial facilities, wastewater treatment facilities, and roads, bridges, and other structures. Until now, streamflow statistics for data-collection stations have often been difficult to obtain because they are scattered among many reports, some of which are not readily available to the public. In addition, streamflow statistics are often needed for locations where no data are available. STREAMSTATS helps solve these problems. STREAMSTATS was developed jointly by the USGS and MassGIS, the State Geographic Information Systems (GIS) agency, in cooperation with the Massachusetts Departments of Environmental Management and Environmental Protection. The application consists of three major components: (1) a user interface that displays maps and allows users to select stream locations for which they want streamflow statistics (fig. 1), (2) a data base of previously published streamflow statistics and descriptive information for 725 USGS data
International Nuclear Information System (INIS)
Dumonteil, E.; Diop, C.M.
2011-01-01
External linking scripts between Monte Carlo transport codes and burnup codes, and complete integration of burnup capability into Monte Carlo transport codes, have been or are currently being developed. Monte Carlo linked burnup methodologies may serve as an excellent benchmark for new deterministic burnup codes used for advanced systems; however, there are some instances where deterministic methodologies break down (i.e., heavily angularly biased systems containing exotic materials without proper group structure) and Monte Carlo burn up may serve as an actual design tool. Therefore, researchers are also developing these capabilities in order to examine complex, three-dimensional exotic material systems that do not contain benchmark data. Providing a reference scheme implies being able to associate statistical errors to any neutronic value of interest like k(eff), reaction rates, fluxes, etc. Usually in Monte Carlo, standard deviations are associated with a particular value by performing different independent and identical simulations (also referred to as 'cycles', 'batches', or 'replicas'), but this is only valid if the calculation itself is not biased. And, as will be shown in this paper, there is a bias in the methodology that consists of coupling transport and depletion codes because Bateman equations are not linear functions of the fluxes or of the reaction rates (those quantities being always measured with an uncertainty). Therefore, we have to quantify and correct this bias. This will be achieved by deriving an unbiased minimum variance estimator of a matrix exponential function of a normal mean. The result is then used to propose a reference scheme to solve Boltzmann/Bateman coupled equations, thanks to Monte Carlo transport codes. Numerical tests will be performed with an ad hoc Monte Carlo code on a very simple depletion case and will be compared to the theoretical results obtained with the reference scheme. Finally, the statistical error propagation
Ahmed, Kazi Farzan; Wang, Guiling; Silander, John; Wilson, Adam M.; Allen, Jenica M.; Horton, Radley; Anyah, Richard
2013-01-01
Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1/8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.
Mattei, Jean-Luc; Le, Cong Nha; Chevalier, Alexis; Maalouf, Azar; Noutehou, Nathan; Queffelec, Patrick; Laur, Vincent
2018-04-01
An efficient and inexpensive process is presented that produces highly oriented bulk compacts made of BaM particles. Barium hexaferrite particles (BaM, nominal composition BaFe11O19) were prepared by a chemical coprecipitation method, using different rates and types of precipitating agents (NaOH and Na2CO3). It was demonstrated that when a large excess of Na2CO3 is used, a noteworthy packing of hexagonal BaM platelets is obtained, after mechanical compaction and firing at moderate temperature (1140 °C), without including any more steps than those required for a conventional sintering process. The hysteresis loop displays a very competitive squareness of 0.88 (normalized remanent magnetization) and a coercivity of 215 kA/m, which make this BaM bulk ferrite suitable for self-biased applications.
International Nuclear Information System (INIS)
Antonopoulos-Domis, M.; Mourtzanos, K.
1996-01-01
Estimators of the confidence limits of open loop transfer functions via Multivariate Auto-Regressive (MAR) modelling are not available in the literature. The statistics of open loop transfer functions obtained by MAR modelling are investigated via numerical experiments. A system of known open loop transfer functions is simulated digitally and excited by random number series. The digital signals of the simulated system are then MAR modelled and the open loop transfer functions are estimated. Performing a large number of realizations, mean values and variances of the open loop transfer functions are estimated. It is found that if the record length N of each realization is long enough then the estimates of open loop transfer functions follow normal distribution. The variance of the open loop transfer functions is proportional to 1/N. For MAR processes the asymptotic covariance matrix of the estimate of open loop transfer functions was found in agreement with theoretical prediction. (author)
Affective bias as a rational response to the statistics of rewards and punishments.
Pulcu, Erdem; Browning, Michael
2017-10-04
Affective bias, the tendency to differentially prioritise the processing of negative relative to positive events, is commonly observed in clinical and non-clinical populations. However, why such biases develop is not known. Using a computational framework, we investigated whether affective biases may reflect individuals' estimates of the information content of negative relative to positive events. During a reinforcement learning task, the information content of positive and negative outcomes was manipulated independently by varying the volatility of their occurrence. Human participants altered the learning rates used for the outcomes selectively, preferentially learning from the most informative. This behaviour was associated with activity of the central norepinephrine system, estimated using pupilometry, for loss outcomes. Humans maintain independent estimates of the information content of distinct positive and negative outcomes which may bias their processing of affective events. Normalising affective biases using computationally inspired interventions may represent a novel approach to treatment development.
Use of multivariate statistics to identify unreliable data obtained using CASA.
Martínez, Luis Becerril; Crispín, Rubén Huerta; Mendoza, Maximino Méndez; Gallegos, Oswaldo Hernández; Martínez, Andrés Aragón
2013-06-01
In order to identify unreliable data in a dataset of motility parameters obtained from a pilot study acquired by a veterinarian with experience in boar semen handling, but without experience in the operation of a computer assisted sperm analysis (CASA) system, a multivariate graphical and statistical analysis was performed. Sixteen boar semen samples were aliquoted then incubated with varying concentrations of progesterone from 0 to 3.33 µg/ml and analyzed in a CASA system. After standardization of the data, Chernoff faces were pictured for each measurement, and a principal component analysis (PCA) was used to reduce the dimensionality and pre-process the data before hierarchical clustering. The first twelve individual measurements showed abnormal features when Chernoff faces were drawn. PCA revealed that principal components 1 and 2 explained 63.08% of the variance in the dataset. Values of principal components for each individual measurement of semen samples were mapped to identify differences among treatment or among boars. Twelve individual measurements presented low values of principal component 1. Confidence ellipses on the map of principal components showed no statistically significant effects for treatment or boar. Hierarchical clustering realized on two first principal components produced three clusters. Cluster 1 contained evaluations of the two first samples in each treatment, each one of a different boar. With the exception of one individual measurement, all other measurements in cluster 1 were the same as observed in abnormal Chernoff faces. Unreliable data in cluster 1 are probably related to the operator inexperience with a CASA system. These findings could be used to objectively evaluate the skill level of an operator of a CASA system. This may be particularly useful in the quality control of semen analysis using CASA systems.
DEFF Research Database (Denmark)
Thorson, James T.; Kristensen, Kasper
2016-01-01
Statistical models play an important role in fisheries science when reconciling ecological theory with available data for wild populations or experimental studies. Ecological models increasingly include both fixed and random effects, and are often estimated using maximum likelihood techniques...... configurations of an age-structured population dynamics model. This simulation experiment shows that the epsilon-method and the existing bias-correction method perform equally well in data-rich contexts, but the epsilon-method is slightly less biased in data-poor contexts. We then apply the epsilon......-method to a spatial regression model when estimating an index of population abundance, and compare results with an alternative bias-correction algorithm that involves Markov-chain Monte Carlo sampling. This example shows that the epsilon-method leads to a biologically significant difference in estimates of average...
Directory of Open Access Journals (Sweden)
Chang-Geun Park
2010-12-01
Full Text Available In this study, we compared the precipitable water vapor (PWV data derived from the radiosonde observation data at Sokcho Observatory and the PWV data at Sokcho Global Positioning System (GPS Observatory provided by Korea Astronomy and Space Science Institute, from 0000 UTC, June 1, 2007 to 1200 UTC, May 31, 2009, and analyzed the radiosonde bias between the day and the night. In the scatter diagram of the daytime and nighttime radiosonde PWV data and the GPS PWV data, dry bias was found in the daytime radiosonde observation as known in the previous study. In addition, for all the rainfall events, the tendency that the wet bias of the radiosonde PWV increased as the GPS PWV decreased and the dry bias of the radiosonde PWV increased as the GPS PWV increased was significantly less distinctive in nighttime than in daytime. The quantitative analysis of the bias and error of the radiosonde PWV data showed that the mean bias decreased in the second year, regardless of nighttime or daytime rainfall, and the non-rainfall root mean square error (RMSE was similar to that of the previous studies, while the rainfall RMSE was larger to a certain extent.
Buchanan, Taylor L.; Lohse, Keith R.
2016-01-01
We surveyed researchers in the health and exercise sciences to explore different areas and magnitudes of bias in researchers' decision making. Participants were presented with scenarios (testing a central hypothesis with p = 0.06 or p = 0.04) in a random order and surveyed about what they would do in each scenario. Participants showed significant…
Gómez-Carrasco, Susana; González-Sánchez, Lola; Aguado, Alfredo; Sanz-Sanz, Cristina; Zanchet, Alexandre; Roncero, Octavio
2012-09-07
In this work we present a dynamically biased statistical model to describe the evolution of the title reaction from statistical to a more direct mechanism, using quasi-classical trajectories (QCT). The method is based on the one previously proposed by Park and Light [J. Chem. Phys. 126, 044305 (2007)]. A recent global potential energy surface is used here to calculate the capture probabilities, instead of the long-range ion-induced dipole interactions. The dynamical constraints are introduced by considering a scrambling matrix which depends on energy and determine the probability of the identity/hop/exchange mechanisms. These probabilities are calculated using QCT. It is found that the high zero-point energy of the fragments is transferred to the rest of the degrees of freedom, what shortens the lifetime of H(5)(+) complexes and, as a consequence, the exchange mechanism is produced with lower proportion. The zero-point energy (ZPE) is not properly described in quasi-classical trajectory calculations and an approximation is done in which the initial ZPE of the reactants is reduced in QCT calculations to obtain a new ZPE-biased scrambling matrix. This reduction of the ZPE is explained by the need of correcting the pure classical level number of the H(5)(+) complex, as done in classical simulations of unimolecular processes and to get equivalent quantum and classical rate constants using Rice-Ramsperger-Kassel-Marcus theory. This matrix allows to obtain a ratio of hop/exchange mechanisms, α(T), in rather good agreement with recent experimental results by Crabtree et al. [J. Chem. Phys. 134, 194311 (2011)] at room temperature. At lower temperatures, however, the present simulations predict too high ratios because the biased scrambling matrix is not statistical enough. This demonstrates the importance of applying quantum methods to simulate this reaction at the low temperatures of astrophysical interest.
Gómez-Carrasco, Susana; González-Sánchez, Lola; Aguado, Alfredo; Sanz-Sanz, Cristina; Zanchet, Alexandre; Roncero, Octavio
2012-09-01
In this work we present a dynamically biased statistical model to describe the evolution of the title reaction from statistical to a more direct mechanism, using quasi-classical trajectories (QCT). The method is based on the one previously proposed by Park and Light [J. Chem. Phys. 126, 044305 (2007), 10.1063/1.2430711]. A recent global potential energy surface is used here to calculate the capture probabilities, instead of the long-range ion-induced dipole interactions. The dynamical constraints are introduced by considering a scrambling matrix which depends on energy and determine the probability of the identity/hop/exchange mechanisms. These probabilities are calculated using QCT. It is found that the high zero-point energy of the fragments is transferred to the rest of the degrees of freedom, what shortens the lifetime of H_5^+ complexes and, as a consequence, the exchange mechanism is produced with lower proportion. The zero-point energy (ZPE) is not properly described in quasi-classical trajectory calculations and an approximation is done in which the initial ZPE of the reactants is reduced in QCT calculations to obtain a new ZPE-biased scrambling matrix. This reduction of the ZPE is explained by the need of correcting the pure classical level number of the H_5^+ complex, as done in classical simulations of unimolecular processes and to get equivalent quantum and classical rate constants using Rice-Ramsperger-Kassel-Marcus theory. This matrix allows to obtain a ratio of hop/exchange mechanisms, α(T), in rather good agreement with recent experimental results by Crabtree et al. [J. Chem. Phys. 134, 194311 (2011), 10.1063/1.3587246] at room temperature. At lower temperatures, however, the present simulations predict too high ratios because the biased scrambling matrix is not statistical enough. This demonstrates the importance of applying quantum methods to simulate this reaction at the low temperatures of astrophysical interest.
ZnO crystals obtained by electrodeposition: Statistical analysis of most important process variables
International Nuclear Information System (INIS)
Cembrero, Jesus; Busquets-Mataix, David
2009-01-01
In this paper a comparative study by means of a statistical analysis of the main process variables affecting ZnO crystal electrodeposition is presented. ZnO crystals were deposited on two different substrates, silicon wafer and indium tin oxide. The control variables were substrate types, electrolyte concentration, temperature, exposition time and current density. The morphologies of the different substrates were observed using scanning electron microscopy. The percentage of substrate area covered by ZnO deposit was calculated by computational image analysis. The design of the applied experiments was based on a two-level factorial analysis involving a series of 32 experiments and an analysis of variance. Statistical results reveal that variables exerting a significant influence on the area covered by ZnO deposit are electrolyte concentration, substrate type and time of deposition, together with a combined two-factor interaction between temperature and current density. However, morphology is also influenced by surface roughness of the substrates
Statistical study on the self-selection bias in FDG-PET cancer screening by a questionnaire survey
International Nuclear Information System (INIS)
Kita, Tamotsu; Yano, Fuzuki; Watanabe, Sadahiro; Soga, Shigeyoshi; Hama, Yukihiro; Shinmoto, Hiroshi; Kosuda, Shigeru
2008-01-01
A questionnaire survey was performed to investigate the possible presence of self-selection bias in 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) cancer screening (PET cancer screening). Responders to the questionnaires survey consisted of 80 healthy persons, who answered whether they undergo PET cancer screening, health consciousness, age, sex, and smoking history. The univariate and multivariate analyses on the four parameters were performed between the responders who were to undergo PET cancer screening and the responders who were not. Statistically significant difference was found in health consciousness between the above-mentioned two groups by both univariate and multivariate analysis with the odds ratio of 2.088. The study indicated that self-selection bias should exist in PET cancer screening. (author)
The Use of Official Statistics in Self-Selection Bias Modeling
Directory of Open Access Journals (Sweden)
Dalla Valle Luciana
2016-12-01
Full Text Available Official statistics are a fundamental source of publicly available information that periodically provides a great amount of data on all major areas of citizens’ lives, such as economics, social development, education, and the environment. However, these extraordinary sources of information are often neglected, especially by business and industrial statisticians. In particular, data collected from small businesses, like small and medium-sized enterprizes (SMEs, are rarely integrated with official statistics data.
Zhu, Jian-Rong; Li, Jian; Zhang, Chun-Mei; Wang, Qin
2017-10-01
The decoy-state method has been widely used in commercial quantum key distribution (QKD) systems. In view of the practical decoy-state QKD with both source errors and statistical fluctuations, we propose a universal model of full parameter optimization in biased decoy-state QKD with phase-randomized sources. Besides, we adopt this model to carry out simulations of two widely used sources: weak coherent source (WCS) and heralded single-photon source (HSPS). Results show that full parameter optimization can significantly improve not only the secure transmission distance but also the final key generation rate. And when taking source errors and statistical fluctuations into account, the performance of decoy-state QKD using HSPS suffered less than that of decoy-state QKD using WCS.
Dagnall, Neil; Denovan, Andrew; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter
2016-01-01
The present paper examined relationships between schizotypy (measured by the Oxford-Liverpool Inventory of Feelings and Experience; O-LIFE scale brief), belief in the paranormal (assessed via the Revised Paranormal Belief Scale; RPBS) and proneness to statistical bias (i.e., perception of randomness and susceptibility to conjunction fallacy). Participants were 254 volunteers recruited via convenience sampling. Probabilistic reasoning problems appeared framed within both standard and paranormal contexts. Analysis revealed positive correlations between the Unusual Experience (UnExp) subscale of O-LIFE and paranormal belief measures [RPBS full scale, traditional paranormal beliefs (TPB) and new age philosophy]. Performance on standard problems correlated negatively with UnExp and belief in the paranormal (particularly the TPB dimension of the RPBS). Consideration of specific problem types revealed that perception of randomness associated more strongly with belief in the paranormal than conjunction; both problem types related similarly to UnExp. Structural equation modeling specified that belief in the paranormal mediated the indirect relationship between UnExp and statistical bias. For problems presented in a paranormal context a framing effect occurred. Whilst UnExp correlated positively with conjunction proneness (controlling for perception of randomness), there was no association between UnExp and perception of randomness (controlling for conjunction).
Directory of Open Access Journals (Sweden)
Neil Dagnall
2016-07-01
Full Text Available The present paper examined relationships between schizotypy (measured by the Oxford-Liverpool Inventory of Feelings and Experience; O-LIFE scale brief, belief in the paranormal (assessed via the Revised Paranormal Belief Scale; RPBS and proneness to statistical bias (i.e., perception of randomness and susceptibility to conjunction fallacy. Participants were 254 volunteers recruited via convenience sampling. Probabilistic reasoning problems appeared framed within both standard and paranormal contexts. Analysis revealed positive correlations between the Unusual Experience subscale of O-LIFE and paranormal belief measures (RPBS full scale, traditional paranormal beliefs and new age philosophy. Performance on standard problems correlated negatively with Unusual Experience and belief in the paranormal (particularly the traditional paranormal belief dimension of the RPBS. Consideration of specific problem types revealed that perception of randomness associated more strongly with belief in the paranormal than conjunction; both problem types related similarly to Unusual Experience. Structural equation modelling specified that belief in the paranormal mediated the indirect relationship between Unusual Experience and statistical bias. For problems presented in a paranormal context a framing effect occurred. Whilst Unusual Experience correlated positively with conjunction proneness (controlling for perception of randomness, there was no association between Unusual Experience and perception of randomness (controlling for conjunction.
The Use of Official Statistics in Self-Selection Bias Modeling
Dalla Valle, L
2016-01-01
Official statistics are a fundamental source of publicly available information that periodically provides a great amount of data on all major areas of citizens’ lives, such as economics, social development, education, and the environment. However, these extraordinary sources of information are often neglected, especially by business and industrial statisticians. In particular, data collected from small businesses, like small and medium-sized enterprizes (SMEs), are rarely integrated with offi...
Yoshioka, S; Aso, Y; Takeda, Y
1990-06-01
Accelerated stability data obtained at a single temperature is statistically evaluated, and the utility of such data for assessment of stability is discussed focussing on the chemical stability of solution-state dosage forms. The probability that the drug content of a product is observed to be within the lower specification limit in the accelerated test is interpreted graphically. This probability depends on experimental errors in the assay and temperature control, as well as the true degradation rate and activation energy. Therefore, the observation that the drug content meets the specification in the accelerated testing can provide only limited information on the shelf-life of the drug, without the knowledge of the activation energy and the accuracy and precision of the assay and temperature control.
Effect of substrate bias on structure and properties of the TiN coatings obtained in the PVD process
International Nuclear Information System (INIS)
Dobrzanski, L.A.; Kwasny, W.
2003-01-01
The paper presents investigation results of the field of deposition parameters on structure and mechanical properties of the TiN coatings obtained by magnetron sputtering in the vacuum furnace onto the ASP 30 sintered high speed steel. Effect of sputtering parameters on chemical and phase composition, thickness, microhardness and roughness parameter. The characteristic structure and surface topography of the analyzed coatings are presented. (author)
Directory of Open Access Journals (Sweden)
Vickers Andrew J
2008-11-01
Full Text Available Abstract Background A common feature of diagnostic research is that results for a diagnostic gold standard are available primarily for patients who are positive for the test under investigation. Data from such studies are subject to what has been termed "verification bias". We evaluated statistical methods for verification bias correction when there are few false negatives. Methods A simulation study was conducted of a screening study subject to verification bias. We compared estimates of the area-under-the-curve (AUC corrected for verification bias varying both the rate and mechanism of verification. Results In a single simulated data set, varying false negatives from 0 to 4 led to verification bias corrected AUCs ranging from 0.550 to 0.852. Excess variation associated with low numbers of false negatives was confirmed in simulation studies and by analyses of published studies that incorporated verification bias correction. The 2.5th – 97.5th centile range constituted as much as 60% of the possible range of AUCs for some simulations. Conclusion Screening programs are designed such that there are few false negatives. Standard statistical methods for verification bias correction are inadequate in this circumstance.
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
Gómez-Carrasco, Susana; González-Sánchez, Lola; Aguado, Alfredo; Sanz-Sanz, Cristina; Zanchet, Alexandre; Roncero, Octavio
2012-01-01
In this work we present a dynamically biased statistical model to describe the evolution of the title reaction from statistical to a more direct mechanism, using quasi-classical trajectories (QCT). The method is based on the one previously proposed by Park and Light [J. Chem. Phys. 126, 044305 (2007)10.1063/1.2430711]. A recent global potential energy surface is used here to calculate the capture probabilities, instead of the long-range ion-induced dipole interactions. The dynamical constrain...
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
Directory of Open Access Journals (Sweden)
Haydee Salmun
2015-02-01
Full Text Available The present study extends the applicability of a statistical model for prediction of storm surge originally developed for The Battery, NY in two ways: I. the statistical model is used as a biascorrection for operationally produced dynamical surge forecasts, and II. the statistical model is applied to the region of the east coast of the U.S. susceptible to winter extratropical storms. The statistical prediction is based on a regression relation between the “storm maximum” storm surge and the storm composite significant wave height predicted ata nearby location. The use of the statistical surge prediction as an alternative bias correction for the National Oceanic and Atmospheric Administration (NOAA operational storm surge forecasts is shownhere to be statistically equivalent to the existing bias correctiontechnique and potentially applicable for much longer forecast lead times as well as for storm surge climate prediction. Applying the statistical model to locations along the east coast shows that the regression relation can be “trained” with data from tide gauge measurements and near-shore buoys along the coast from North Carolina to Maine, and that it provides accurate estimates of storm surge.
International Nuclear Information System (INIS)
Giannantonio, Tommaso; Porciani, Cristiano
2010-01-01
We study structure formation in the presence of primordial non-Gaussianity of the local type with parameters f NL and g NL . We show that the distribution of dark-matter halos is naturally described by a multivariate bias scheme where the halo overdensity depends not only on the underlying matter density fluctuation δ but also on the Gaussian part of the primordial gravitational potential φ. This corresponds to a non-local bias scheme in terms of δ only. We derive the coefficients of the bias expansion as a function of the halo mass by applying the peak-background split to common parametrizations for the halo mass function in the non-Gaussian scenario. We then compute the halo power spectrum and halo-matter cross spectrum in the framework of Eulerian perturbation theory up to third order. Comparing our results against N-body simulations, we find that our model accurately describes the numerical data for wave numbers k≤0.1-0.3h Mpc -1 depending on redshift and halo mass. In our multivariate approach, perturbations in the halo counts trace φ on large scales, and this explains why the halo and matter power spectra show different asymptotic trends for k→0. This strongly scale-dependent bias originates from terms at leading order in our expansion. This is different from what happens using the standard univariate local bias where the scale-dependent terms come from badly behaved higher-order corrections. On the other hand, our biasing scheme reduces to the usual local bias on smaller scales, where |φ| is typically much smaller than the density perturbations. We finally discuss the halo bispectrum in the context of multivariate biasing and show that, due to its strong scale and shape dependence, it is a powerful tool for the detection of primordial non-Gaussianity from future galaxy surveys.
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
Levy, David M; Peart, Sandra J
2008-06-01
We wish to deal with investigator bias in a statistical context. We sketch how a textbook solution to the problem of "outliers" which avoids one sort of investigator bias, creates the temptation for another sort. We write down a model of the approbation seeking statistician who is tempted by sympathy for client to violate the disciplinary standards. We give a simple account of one context in which we might expect investigator bias to flourish. Finally, we offer tentative suggestions to deal with the problem of investigator bias which follow from our account. As we have given a very sparse and stylized account of investigator bias, we ask what might be done to overcome this limitation.
Directory of Open Access Journals (Sweden)
V. K. Hohlov
2014-01-01
Full Text Available The article studies a neural network approach to obtain the statistical characteristics of the input vector implementations of signal and noise at ill-conditioned matrices of correlation moments to solve the problems to select and reduce the vector dimensions of informative features at detection and recognition of signals and noise based on regression methods.A scientific novelty is determined by applying neural network algorithms for the efficient solution of problems to select the informative features and determine the parameters of regression algorithms in terms of the degeneracy or ill-conditioned data with unknown expectation and covariance matrices.The article proposes to use a single-layer neural network with no zero weights and activation functions to calculate the initial regression characteristics and the mean-square value error of multiple initial regression representations, which are necessary to justify the selection of informative features, reduce a dimension of sign vectors and implement the regression algorithms. It is shown that when excluding direct links between the inputs and their corresponding neurons, in the training network the weight coefficients of neuron inputs are the coefficients of initial multiple regression, the error meansquare value of multiple initial regression representations is calculated at the outputs of neurons. The article considers conditionality of the problem to calculate the matrix that is inverse one for matrix of correlation moments. It defines a condition number, which characterizes the relative error of stated task.The problem concerning the matrix condition of the correlation moment of informative signal features and noise arises when solving the problem to find the multiple coefficients of initial regression (MCIR and the residual mean-square values of the multiple regression representations. For obtaining the MCIR and finding the residual mean-square values the matrix of correlation moments of
Links to sources of cancer-related statistics, including the Surveillance, Epidemiology and End Results (SEER) Program, SEER-Medicare datasets, cancer survivor prevalence data, and the Cancer Trends Progress Report.
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
International Nuclear Information System (INIS)
2001-01-01
For the year 2000, 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 1999, Statistics Finland, Helsinki 2000, 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 from the use of fossil fuels, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in 2000, Energy exports by recipient country in 2000, 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
International Nuclear Information System (INIS)
2000-01-01
For the year 1999 and 2000, 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-March 2000, Energy exports by recipient country in January-March 2000, 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
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
Collados-Lara, Antonio-Juan; Pulido-Velazquez, David; Pardo-Iguzquiza, Eulogio
2017-04-01
Assessing impacts of potential future climate change scenarios in precipitation and temperature is essential to design adaptive strategies in water resources systems. The objective of this work is to analyze the possibilities of different statistical downscaling methods to generate future potential scenarios in an Alpine Catchment from historical data and the available climate models simulations performed in the frame of the CORDEX EU project. The initial information employed to define these downscaling approaches are the historical climatic data (taken from the Spain02 project for the period 1971-2000 with a spatial resolution of 12.5 Km) and the future series provided by climatic models in the horizon period 2071-2100 . We have used information coming from nine climate model simulations (obtained from five different Regional climate models (RCM) nested to four different Global Climate Models (GCM)) from the European CORDEX project. In our application we have focused on the Representative Concentration Pathways (RCP) 8.5 emissions scenario, which is the most unfavorable scenario considered in the fifth Assessment Report (AR5) by the Intergovernmental Panel on Climate Change (IPCC). For each RCM we have generated future climate series for the period 2071-2100 by applying two different approaches, bias correction and delta change, and five different transformation techniques (first moment correction, first and second moment correction, regression functions, quantile mapping using distribution derived transformation and quantile mapping using empirical quantiles) for both of them. Ensembles of the obtained series were proposed to obtain more representative potential future climate scenarios to be employed to study potential impacts. In this work we propose a non-equifeaseble combination of the future series giving more weight to those coming from models (delta change approaches) or combination of models and techniques that provides better approximation to the basic
International Nuclear Information System (INIS)
2003-01-01
For the year 2002, part of the figures shown in the tables of the Energy Review are partly preliminary. The annual statistics of the Energy Review also includes historical time-series over a longer period (see e.g. Energiatilastot 2001, Statistics Finland, Helsinki 2002). The applied energy units and conversion coefficients are shown in the inside 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, Supply 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 Excise taxes, precautionary stock fees on oil pollution fees on energy products
International Nuclear Information System (INIS)
2004-01-01
For the year 2003 and 2004, the figures shown in the tables of the Energy Review are partly preliminary. The annual statistics of the Energy Review also includes historical time-series over a longer period (see e.g. Energiatilastot, Statistics Finland, Helsinki 2003, ISSN 0785-3165). The applied energy units and conversion coefficients are shown in the inside 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-March 2004, Energy exports by recipient country in January-March 2004, 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 Excise taxes, precautionary stock fees on oil pollution fees
International Nuclear Information System (INIS)
2000-01-01
For the year 1999 and 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy also includes historical time series over a longer period (see e.g., Energiatilastot 1999, Statistics Finland, Helsinki 2000, 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 2000, Energy exports by recipient country in January-June 2000, 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
Energy Technology Data Exchange (ETDEWEB)
Panka, Istvan; Hegyi, Gyoergy; Maraczy, Csaba; Temesvari, Emese [Hungarian Academy of Sciences, Budapest (Hungary). Reactor Analysis Dept.
2017-11-15
The best-estimate KARATE code system has been widely used for core design calculations and simulations of slow transients of VVER reactors. Recently there has been an increasing need for assessing the uncertainties of such calculations by propagating the basic input uncertainties of the models through the full calculation chain. In order to determine the uncertainties of quantities of interest during the burnup, the statistical version of the KARATE code system has been elaborated. In the first part of the paper, the main features of the new code system are discussed. The applied statistical method is based on Monte-Carlo sampling of the considered input data taking into account mainly the covariance matrices of the cross sections and/or the technological uncertainties. In the second part of the paper, only the uncertainties of cross sections are considered and an equilibrium cycle related to a VVER-440 type reactor is investigated. The burnup dependence of the uncertainties of some safety related parameters (e.g. critical boron concentration, rod worth, feedback coefficients, assembly-wise radial power and burnup distribution) are discussed and compared to the recently used limits.
International Nuclear Information System (INIS)
Fazakerley, J.; Charnock, P.; Wilde, R.; Jones, R.; Ward, M.
2010-01-01
For the purpose of patient dose audit, clinical audit and radiology workload analysis, data from Radiology Information Systems (RIS) at many hospitals are collected using a database and the analysis was automated using a statistical package and Visual Basic coding. The database is a Structured Query Language database, which can be queried using an off-the-shelf statistical package, Statistica. Macros were created to automatically format the data to a consistent format between different hospitals ready for analysis. These macros can also be used to automate further analysis such as detailing mean kV, mAs and entrance surface dose per room and per gender. Standard deviation and standard error of the mean are also generated. Graphs can also be generated to illustrate the trends in doses between different variables such as room and gender. Collectively, this information can be used to generate a report. A process that once could take up to 1 d to complete now takes around 1 h. A major benefit in providing the service to hospital trusts is that less resource is now required to report on RIS data, making the possibility of continuous dose audit more likely. Time that was spent on sorting through data can now be spent on improving the analysis to provide benefit to the customer. Using data sets from RIS is a good way to perform dose audits as the huge numbers of data available provide the bases for very accurate analysis. Using macros written in Statistica Visual Basic has helped sort and consistently analyse these data. Being able to analyse by exposure factors has provided a more detailed report to the customer. (authors)
What is the ARM Climate Research Facility: Is Global Warming a Real Bias or a Statistical Anomaly?
Energy Technology Data Exchange (ETDEWEB)
Egami, Takeshi [U of Tennessee and ORNL; Sisterson, Douglas L.
2010-03-10
The Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) is a U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research national user facility. With multi-laboratory management of distributed facilities worldwide, the ACRF does not fit the mold of a traditional user facility located at a national laboratory. The ACRF provides the world's most comprehensive 24/7 observational capabilities for obtaining atmospheric data specifically for climate change research. Serving nearly 5,000 registered users from 15 federal and state agencies, 375 universities, and 67 countries, the ACRF Data Archive collects and delivers over 5 terabytes of data per month to its users. The ACRF users provide critical information about cloud formation processes, water vapor, and aerosols, and their influence on radiative transfer in the atmosphere. This information is used to improve global climate model predictions of climate change.
Wallace, Lorraine S; Chisolm, Deena J; Abdel-Rasoul, Mahmoud; DeVoe, Jennifer E
2013-08-01
This study examined adults' self-reported understanding and formatting preferences of medical statistics, confidence in self-care and ability to obtain health advice or information, and perceptions of patient-health-care provider communication measured through dual survey modes (random digital dial and mail). Even while controlling for sociodemographic characteristics, significant differences in regard to adults' responses to survey variables emerged as a function of survey mode. While the analyses do not allow us to pinpoint the underlying causes of the differences observed, they do suggest that mode of administration should be carefully adjusted for and considered.
Directory of Open Access Journals (Sweden)
Haruki Nakamura
2012-09-01
Full Text Available We have developed a method for estimating protein-ligand binding free energy (DG based on the direct protein-ligand interaction obtained by a molecular dynamics simulation. Using this method, we estimated the DG value statistically by the average values of the van der Waals and electrostatic interactions between each amino acid of the target protein and the ligand molecule. In addition, we introduced fluctuations in the accessible surface area (ASA and dihedral angles of the protein-ligand complex system as the entropy terms of the DG estimation. The present method included the fluctuation term of structural change of the protein and the effective dielectric constant. We applied this method to 34 protein-ligand complex structures. As a result, the correlation coefficient between the experimental and calculated DG values was 0.81, and the average error of DG was 1.2 kcal/mol with the use of the fixed parameters. These results were obtained from a 2 nsec molecular dynamics simulation.
Lewis, Rebecca; Liddick, Sean; Spyrou, Artemis; Crider, Benjamin; Dombos, Alexander; Naqvi, Farheen; Prokop, Christopher; Quinn, Stephen; Larsen, Ann-Cecilie; Crespo Campo, Lucia; Guttormsen, Magne; Renstrom, Therese; Siem, Sunniva; Bleuel, Darren; Couture, Aaron; Mosby, Shea; Perdikakis, George
2017-09-01
A majority of the abundance of the elements above iron are produced by neutron capture reactions, and, in explosive stellar processes, many of these reactions take place on unstable nuclei. Direct neutron capture experiments can only be performed on stable and long-lived nuclei, requiring indirect methods for the remaining isotopes. Statistical neutron capture can be described using the nuclear level density (NLD), the γ strength function (γSF), and an optical model. The NLD and γSF can be obtained using the β-Oslo method. The NLD and γSF were recently determined for 74Zn using the β-Oslo method, and were used in both TALYS and CoH to calculate the 73Zn(n, γ)74Zn neutron capture cross section. The cross sections calculated in TALYS and CoH are expected to be identical if the inputs for both codes are the same, however, after a thorough investigation into the inputs for the 73Zn(n, γ)74Zn reaction there is still a factor of two discrepancy between the two codes.
Energy Technology Data Exchange (ETDEWEB)
Gamble, Jennifer; Lagravere, Manuel O.; Major, Paul W.; Heo, Giseon [University of Alberta, Edmonton (Canada)
2012-03-15
To describe a statistical method of three-dimensional landmark configuration data and apply it to an orthodontic data set comparing two types of rapid maxillary expansion (RME) treatments. Landmark configurations obtained from cone beam CT scans were used to represent patients in two types (please describe what were two types) of RME groups and a control group over four time points. A method using tools from persistent homology and dimensionality reduction is presented and used to identify variability between the subjects. The analysis was in agreement with previous results using conventional methods, which found significant differences between treatment groups and the control, but no distinction between the types of treatment. Additionally, it was found that second molar eruption varied considerably between the subjects, and this has not been evaluated in previous analyses. This method of analysis allows entire configurations to be considered as a whole, and does not require specific inter-landmark distances or angles to be selected. Sources of variability present themselves, without having to be individually sought after. This method is suggested as an additional tool for the analysis of landmark configuration data.
Energy Technology Data Exchange (ETDEWEB)
Blin, A; Le Ber, J
1966-07-01
This document provides results obtained on many samples of transistors irradiated in the laboratories of the Institut of Nuclear Physic of Lyon. The physical aspects of the irradiation,the statistical aspects of the study and the reliability under irradiation have been studied, but the accent is done on the statistical analysis. (A.L.B.)
Liu, Tianyi; Nie, Xiaolu; Wu, Zehao; Zhang, Ying; Feng, Guoshuang; Cai, Siyu; Lv, Yaqi; Peng, Xiaoxia
2017-12-29
Different confounder adjustment strategies were used to estimate odds ratios (ORs) in case-control study, i.e. how many confounders original studies adjusted and what the variables are. This secondary data analysis is aimed to detect whether there are potential biases caused by difference of confounding factor adjustment strategies in case-control study, and whether such bias would impact the summary effect size of meta-analysis. We included all meta-analyses that focused on the association between breast cancer and passive smoking among non-smoking women, as well as each original case-control studies included in these meta-analyses. The relative deviations (RDs) of each original study were calculated to detect how magnitude the adjustment would impact the estimation of ORs, compared with crude ORs. At the same time, a scatter diagram was sketched to describe the distribution of adjusted ORs with different number of adjusted confounders. Substantial inconsistency existed in meta-analysis of case-control studies, which would influence the precision of the summary effect size. First, mixed unadjusted and adjusted ORs were used to combine individual OR in majority of meta-analysis. Second, original studies with different adjustment strategies of confounders were combined, i.e. the number of adjusted confounders and different factors being adjusted in each original study. Third, adjustment did not make the effect size of original studies trend to constringency, which suggested that model fitting might have failed to correct the systematic error caused by confounding. The heterogeneity of confounder adjustment strategies in case-control studies may lead to further bias for summary effect size in meta-analyses, especially for weak or medium associations so that the direction of causal inference would be even reversed. Therefore, further methodological researches are needed, referring to the assessment of confounder adjustment strategies, as well as how to take this kind
Energy Technology Data Exchange (ETDEWEB)
Pereira, Joao Eduardo da Silva [Universidade Federal de Santa Maria (UFSM), RS (Brazil). Dept. de Estatistica]. E-mail: jesp61@gmail.com; Silva, Jose Luiz Silverio da; Pires, Carlos Alberto da Fonseca [Universidade Federal de Santa Maria (UFSM), RS (Brazil). Lab. de Hidrogeologia; Strieder, Adelir Jose [Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS (Brazil). Lab. de Modelagem Geologica e Ambiental
2007-07-01
The present work was developed in outcrops of Santa Maria region, southern Brazil, Rio Grande do Sul State. Statistic evaluations were applied in different rock types. The possibility to distinguish different geologic units, sedimentary and volcanic (acid and basic types) by means of the statistic analyses from the use of airborne gamma-ray spectrometry integrating potash radiation emissions data with geological and geochemistry data is discussed. This Project was carried out at 1973 by Geological Survey of Brazil/Companhia de Pesquisas de Recursos Minerais. The Camaqua Project evaluated the behavior of potash concentrations generating XYZ Geosof 1997 format, one grid, thematic map and digital thematic map files from this total area. Using these data base, the integration of statistics analyses in sedimentary formations which belong to the Depressao Central do Rio Grande do Sul and/or to volcanic rocks from Planalto da Serra Geral at the border of Parana Basin was tested. Univariate statistics model was used: the media, the standard media error, and the trust limits were estimated. The Tukey's Test was used in order to compare mean values. The results allowed to create criteria to distinguish geological formations based on their potash content. The back-calibration technique was employed to transform K radiation to percentage. Inside this context it was possible to define characteristic values from radioactive potash emissions and their trust ranges in relation to geologic formations. The potash variable when evaluated in relation to geographic Universal Transverse Mercator coordinates system showed a spatial relation following one polynomial model of second order, with one determination coefficient. The statistica 7.1 software Generalist Linear Models produced by Statistics Department of Federal University of Santa Maria/Brazil was used. (author)
Yuan, Ye; Ries, Ludwig; Petermeier, Hannes; Steinbacher, Martin; Gómez-Peláez, Angel J.; Leuenberger, Markus C.; Schumacher, Marcus; Trickl, Thomas; Couret, Cedric; Meinhardt, Frank; Menzel, Annette
2018-03-01
Critical data selection is essential for determining representative baseline levels of atmospheric trace gases even at remote measurement sites. Different data selection techniques have been used around the world, which could potentially lead to reduced compatibility when comparing data from different stations. This paper presents a novel statistical data selection method named adaptive diurnal minimum variation selection (ADVS) based on CO2 diurnal patterns typically occurring at elevated mountain stations. Its capability and applicability were studied on records of atmospheric CO2 observations at six Global Atmosphere Watch stations in Europe, namely, Zugspitze-Schneefernerhaus (Germany), Sonnblick (Austria), Jungfraujoch (Switzerland), Izaña (Spain), Schauinsland (Germany), and Hohenpeissenberg (Germany). Three other frequently applied statistical data selection methods were included for comparison. Among the studied methods, our ADVS method resulted in a lower fraction of data selected as a baseline with lower maxima during winter and higher minima during summer in the selected data. The measured time series were analyzed for long-term trends and seasonality by a seasonal-trend decomposition technique. In contrast to unselected data, mean annual growth rates of all selected datasets were not significantly different among the sites, except for the data recorded at Schauinsland. However, clear differences were found in the annual amplitudes as well as the seasonal time structure. Based on a pairwise analysis of correlations between stations on the seasonal-trend decomposed components by statistical data selection, we conclude that the baseline identified by the ADVS method is a better representation of lower free tropospheric (LFT) conditions than baselines identified by the other methods.
Directory of Open Access Journals (Sweden)
Y. Yuan
2018-03-01
Full Text Available Critical data selection is essential for determining representative baseline levels of atmospheric trace gases even at remote measurement sites. Different data selection techniques have been used around the world, which could potentially lead to reduced compatibility when comparing data from different stations. This paper presents a novel statistical data selection method named adaptive diurnal minimum variation selection (ADVS based on CO2 diurnal patterns typically occurring at elevated mountain stations. Its capability and applicability were studied on records of atmospheric CO2 observations at six Global Atmosphere Watch stations in Europe, namely, Zugspitze-Schneefernerhaus (Germany, Sonnblick (Austria, Jungfraujoch (Switzerland, Izaña (Spain, Schauinsland (Germany, and Hohenpeissenberg (Germany. Three other frequently applied statistical data selection methods were included for comparison. Among the studied methods, our ADVS method resulted in a lower fraction of data selected as a baseline with lower maxima during winter and higher minima during summer in the selected data. The measured time series were analyzed for long-term trends and seasonality by a seasonal-trend decomposition technique. In contrast to unselected data, mean annual growth rates of all selected datasets were not significantly different among the sites, except for the data recorded at Schauinsland. However, clear differences were found in the annual amplitudes as well as the seasonal time structure. Based on a pairwise analysis of correlations between stations on the seasonal-trend decomposed components by statistical data selection, we conclude that the baseline identified by the ADVS method is a better representation of lower free tropospheric (LFT conditions than baselines identified by the other methods.
International Nuclear Information System (INIS)
Veglia, A.
1981-08-01
In cases where sets of data are obviously not normally distributed, the application of a nonparametric method for the estimation of a confidence interval for the mean seems to be more suitable than some other methods because such a method requires few assumptions about the population of data. A two-step statistical method is proposed which can be applied to any set of analytical results: elimination of outliers by a nonparametric method based on Tchebycheff's inequality, and determination of a confidence interval for the mean by a non-parametric method based on binominal distribution. The method is appropriate only for samples of size n>=10
Highton, R
1993-12-01
An analysis of the relationship between the number of loci utilized in an electrophoretic study of genetic relationships and the statistical support for the topology of UPGMA trees is reported for two published data sets. These are Highton and Larson (Syst. Zool.28:579-599, 1979), an analysis of the relationships of 28 species of plethodonine salamanders, and Hedges (Syst. Zool., 35:1-21, 1986), a similar study of 30 taxa of Holarctic hylid frogs. As the number of loci increases, the statistical support for the topology at each node in UPGMA trees was determined by both the bootstrap and jackknife methods. The results show that the bootstrap and jackknife probabilities supporting the topology at some nodes of UPGMA trees increase as the number of loci utilized in a study is increased, as expected for nodes that have groupings that reflect phylogenetic relationships. The pattern of increase varies and is especially rapid in the case of groups with no close relatives. At nodes that likely do not represent correct phylogenetic relationships, the bootstrap probabilities do not increase and often decline with the addition of more loci.
An experimental verification of laser-velocimeter sampling bias and its correction
Johnson, D. A.; Modarress, D.; Owen, F. K.
1982-01-01
The existence of 'sampling bias' in individual-realization laser velocimeter measurements is experimentally verified and shown to be independent of sample rate. The experiments were performed in a simple two-stream mixing shear flow with the standard for comparison being laser-velocimeter results obtained under continuous-wave conditions. It is also demonstrated that the errors resulting from sampling bias can be removed by a proper interpretation of the sampling statistics. In addition, data obtained in a shock-induced separated flow and in the near-wake of airfoils are presented, both bias-corrected and uncorrected, to illustrate the effects of sampling bias in the extreme.
Energy Technology Data Exchange (ETDEWEB)
Jammet, H; Perrissin, F [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires
1959-07-01
These statistics deal with the doses due to external exposure received by the monitored workers of the French Atomic Centers and of other establishments. They allow: - to estimate the value of the accumulated doses with respect to the maximum permissible levels recommended by the I.C.R.P. and to follow their variation over some years. - to arrange the different categories of work by order of hazard with respect to the doses received by the workers while achieving the operations. - to come to the conclusion that it is possible to work in atomic industry without reaching the maximum permissible levels. (author) [French] Ces statistiques portent sur les doses d'irradiation externe recues par le personnel surveille appartenant au Commissariat et a d'autres organismes. Elles permettent: - d'apprecier la valeur des doses cumulees en fonction des normes de la C.I.P.R. ainsi que leur evolution au cours des annees. - de classer les differentes categories de travaux par ordre de risque en fonction des doses recues pendant leur execution. - de conclure a la possibilite de travail dans l'industrie atomique sans que les doses maxima admissibles soient atteintes. (auteur)
Assessing the extent of non-stationary biases in GCMs
Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish
2017-06-01
General circulation models (GCMs) are the main tools for estimating changes in the climate for the future. The imperfect representation of climate models introduces biases in the simulations that need to be corrected prior to their use for impact assessments. Bias correction methods generally assume that the bias calculated over the historical period does not change and can be applied to the future. This study investigates this assumption by considering the extent and nature of bias non-stationarity using 20th century precipitation and temperature simulations from six CMIP5 GCMs across Australia. Four statistics (mean, standard deviation, 10th and 90th quantiles) in monthly and seasonal biases are obtained for three different time window lengths (10, 25 and 33 years) to examine the properties of bias over time. This approach is repeated for two different phases of the Interdecadal Pacific Oscillation (IPO), which is known to have strong influences on the Australian climate. It is found that bias non-stationarity at decadal timescales is indeed an issue over some of Australia for some GCMs. When considering interdecadal variability there are significant difference in the bias between positive and negative phases of the IPO. Regional analyses confirmed these findings with the largest differences seen on the east coast of Australia, where IPO impacts tend to be the strongest. The nature of the bias non-stationarity found in this study suggests that it will be difficult to modify existing bias correction approaches to account for non-stationary biases. A more practical approach for impact assessments that use bias correction maybe to use a selection of GCMs where the assumption of bias non-stationarity holds.
Yücel, Meryem A; Selb, Juliette; Aasted, Christopher M; Petkov, Mike P; Becerra, Lino; Borsook, David; Boas, David A
2015-07-01
Autonomic nervous system response is known to be highly task-dependent. The sensitivity of near-infrared spectroscopy (NIRS) measurements to superficial layers, particularly to the scalp, makes it highly susceptible to systemic physiological changes. Thus, one critical step in NIRS data processing is to remove the contribution of superficial layers to the NIRS signal and to obtain the actual brain response. This can be achieved using short separation channels that are sensitive only to the hemodynamics in the scalp. We investigated the contribution of hemodynamic fluctuations due to autonomous nervous system activation during various tasks. Our results provide clear demonstrations of the critical role of using short separation channels in NIRS measurements to disentangle differing autonomic responses from the brain activation signal of interest.
Last, Carsten
2017-01-01
This book proposes a new approach to handle the problem of limited training data. Common approaches to cope with this problem are to model the shape variability independently across predefined segments or to allow artificial shape variations that cannot be explained through the training data, both of which have their drawbacks. The approach presented uses a local shape prior in each element of the underlying data domain and couples all local shape priors via smoothness constraints. The book provides a sound mathematical foundation in order to embed this new shape prior formulation into the well-known variational image segmentation framework. The new segmentation approach so obtained allows accurate reconstruction of even complex object classes with only a few training shapes at hand.
The Probability Distribution for a Biased Spinner
Foster, Colin
2012-01-01
This article advocates biased spinners as an engaging context for statistics students. Calculating the probability of a biased spinner landing on a particular side makes valuable connections between probability and other areas of mathematics. (Contains 2 figures and 1 table.)
An introduction to Bartlett correction and bias reduction
Cordeiro, Gauss M
2014-01-01
This book presents a concise introduction to Bartlett and Bartlett-type corrections of statistical tests and bias correction of point estimators. The underlying idea behind both groups of corrections is to obtain higher accuracy in small samples. While the main focus is on corrections that can be analytically derived, the authors also present alternative strategies for improving estimators and tests based on bootstrap, a data resampling technique, and discuss concrete applications to several important statistical models.
Harris, Ian
2016-01-01
I read with interest the comment by Mark Wilson in the Indian Journal of Medical Ethics regarding bias and conflicts of interest in medical journals. Wilson targets one journal (the New England Journal of Medicine: NEJM) and one particular "scandal" to make his point that journals' decisions on publication are biased by commercial conflicts of interest (CoIs). It is interesting that he chooses the NEJM which, by his own admission, had one of the strictest CoI policies and had published widely on this topic. The feeling is that if the NEJM can be guilty, they can all be guilty.
DEFF Research Database (Denmark)
Paldam, Martin
is censoring: selection by the size of estimate; SR3 selects the optimal combination of fit and size; and SR4 selects the first satisficing result. The last four SRs are steered by priors and result in bias. The MST and the FAT-PET have been developed for detection and correction of such bias. The simulations......Economic research typically runs J regressions for each selected for publication – it is often selected as the ‘best’ of the regressions. The paper examines five possible meanings of the word ‘best’: SR0 is ideal selection with no bias; SR1 is polishing: selection by statistical fit; SR2...... are made by data variation, while the model is the same. It appears that SR0 generates narrow funnels much at odds with observed funnels, while the other four funnels look more realistic. SR1 to SR4 give the mean a substantial bias that confirms the prior causing the bias. The FAT-PET MRA works well...
Josse Delfgaauw; Michiel Souverijn
2014-01-01
markdownabstract__Abstract__ When verifiable performance measures are imperfect, organizations often resort to subjective performance pay. This may give supervisors the power to direct employees towards tasks that mainly benefit the supervisor rather than the organization. We cast a principal-supervisor-agent model in a multitask setting, where the supervisor has an intrinsic preference towards specific tasks. We show that subjective performance pay based on evaluation by a biased supervisor ...
Statistical analysis of angular correlation measurements
International Nuclear Information System (INIS)
Oliveira, R.A.A.M. de.
1986-01-01
Obtaining the multipole mixing ratio, δ, of γ transitions in angular correlation measurements is a statistical problem characterized by the small number of angles in which the observation is made and by the limited statistic of counting, α. The inexistence of a sufficient statistics for the estimator of δ, is shown. Three different estimators for δ were constructed and their properties of consistency, bias and efficiency were tested. Tests were also performed in experimental results obtained in γ-γ directional correlation measurements. (Author) [pt
Desjacques, Vincent; Jeong, Donghui; Schmidt, Fabian
2018-02-01
This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy statistics. We then review the excursion-set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.
Jeong, Donghui; Desjacques, Vincent; Schmidt, Fabian
2018-01-01
Here, we briefly introduce the key results of the recent review (arXiv:1611.09787), whose abstract is as following. This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy (or halo) statistics. We then review the excursion set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.
Department of Homeland Security — Accident statistics available on the Coast Guard’s website by state, year, and one variable to obtain tables and/or graphs. Data from reports has been loaded for...
Allegheny County / City of Pittsburgh / Western PA Regional Data Center — Data about the usage of the WPRDC site and its various datasets, obtained by combining Google Analytics statistics with information from the WPRDC's data portal.
Statistical electromagnetics: Complex cavities
Naus, H.W.L.
2008-01-01
A selection of the literature on the statistical description of electromagnetic fields and complex cavities is concisely reviewed. Some essential concepts, for example, the application of the central limit theorem and the maximum entropy principle, are scrutinized. Implicit assumptions, biased
Bias against research on gender bias.
Cislak, Aleksandra; Formanowicz, Magdalena; Saguy, Tamar
2018-01-01
The bias against women in academia is a documented phenomenon that has had detrimental consequences, not only for women, but also for the quality of science. First, gender bias in academia affects female scientists, resulting in their underrepresentation in academic institutions, particularly in higher ranks. The second type of gender bias in science relates to some findings applying only to male participants, which produces biased knowledge. Here, we identify a third potentially powerful source of gender bias in academia: the bias against research on gender bias. In a bibliometric investigation covering a broad range of social sciences, we analyzed published articles on gender bias and race bias and established that articles on gender bias are funded less often and published in journals with a lower Impact Factor than articles on comparable instances of social discrimination. This result suggests the possibility of an underappreciation of the phenomenon of gender bias and related research within the academic community. Addressing this meta-bias is crucial for the further examination of gender inequality, which severely affects many women across the world.
Codon Bias Patterns of E. coli's Interacting Proteins.
Directory of Open Access Journals (Sweden)
Maddalena Dilucca
Full Text Available Synonymous codons, i.e., DNA nucleotide triplets coding for the same amino acid, are used differently across the variety of living organisms. The biological meaning of this phenomenon, known as codon usage bias, is still controversial. In order to shed light on this point, we propose a new codon bias index, CompAI, that is based on the competition between cognate and near-cognate tRNAs during translation, without being tuned to the usage bias of highly expressed genes. We perform a genome-wide evaluation of codon bias for E.coli, comparing CompAI with other widely used indices: tAI, CAI, and Nc. We show that CompAI and tAI capture similar information by being positively correlated with gene conservation, measured by the Evolutionary Retention Index (ERI, and essentiality, whereas, CAI and Nc appear to be less sensitive to evolutionary-functional parameters. Notably, the rate of variation of tAI and CompAI with ERI allows to obtain sets of genes that consistently belong to specific clusters of orthologous genes (COGs. We also investigate the correlation of codon bias at the genomic level with the network features of protein-protein interactions in E.coli. We find that the most densely connected communities of the network share a similar level of codon bias (as measured by CompAI and tAI. Conversely, a small difference in codon bias between two genes is, statistically, a prerequisite for the corresponding proteins to interact. Importantly, among all codon bias indices, CompAI turns out to have the most coherent distribution over the communities of the interactome, pointing to the significance of competition among cognate and near-cognate tRNAs for explaining codon usage adaptation. Notably, CompAI may potentially correlate with translation speed measurements, by accounting for the specific delay induced by wobble-pairing between codons and anticodons.
Understanding Statistics - Cancer Statistics
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.
Detection of bias in animal model pedigree indices of heifers
Directory of Open Access Journals (Sweden)
M. LIDAUER
2008-12-01
Full Text Available The objective of the study was to test whether the pedigree indices (PI of heifers are biased, and if so, whether the magnitude of the bias varies in different groups of heifers. Therefore, two animal model evaluations with two different data sets were computed. Data with all the records from the national evaluation in December 1994 was used to obtain estimated breeding values (EBV for 305-days' milk yield and protein yield. In the second evaluation, the PIs were estimated for cows calving the first time in 1993 by excluding all their production records from the data. Three different statistics, a simple t-test, the linear regression of EBV on PI, and the polynomial regression of the difference in the predictions (EBV-PI on PI, were computed for three groups of first parity Ayrshire cows: daughters of proven sires, daughters of young sires, and daughters of bull dam candidates. A practically relevant bias was found only in the PIs for the daughters of young sires. On average their PIs were biased upwards by 0.20 standard deviations (78.8 kg for the milk yield and by 0.21 standard deviations (2.2 kg for the protein yield. The polynomial regression analysis showed that the magnitude of the bias in the PIs changed somewhat with the size of the PIs.;
Adaptable history biases in human perceptual decisions.
Abrahamyan, Arman; Silva, Laura Luz; Dakin, Steven C; Carandini, Matteo; Gardner, Justin L
2016-06-21
When making choices under conditions of perceptual uncertainty, past experience can play a vital role. However, it can also lead to biases that worsen decisions. Consistent with previous observations, we found that human choices are influenced by the success or failure of past choices even in a standard two-alternative detection task, where choice history is irrelevant. The typical bias was one that made the subject switch choices after a failure. These choice history biases led to poorer performance and were similar for observers in different countries. They were well captured by a simple logistic regression model that had been previously applied to describe psychophysical performance in mice. Such irrational biases seem at odds with the principles of reinforcement learning, which would predict exquisite adaptability to choice history. We therefore asked whether subjects could adapt their irrational biases following changes in trial order statistics. Adaptability was strong in the direction that confirmed a subject's default biases, but weaker in the opposite direction, so that existing biases could not be eradicated. We conclude that humans can adapt choice history biases, but cannot easily overcome existing biases even if irrational in the current context: adaptation is more sensitive to confirmatory than contradictory statistics.
Combination of biased forecasts: Bias correction or bias based weights?
Wenzel, Thomas
1999-01-01
Most of the literature on combination of forecasts deals with the assumption of unbiased individual forecasts. Here, we consider the case of biased forecasts and discuss two different combination techniques resulting in an unbiased forecast. On the one hand we correct the individual forecasts, and on the other we calculate bias based weights. A simulation study gives some insight in the situations where we should use the different methods.
Beria, H.; Nanda, T., Sr.; Chatterjee, C.
2015-12-01
High resolution satellite precipitation products such as Tropical Rainfall Measuring Mission (TRMM), Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts (ECMWF), etc., offer a promising alternative to flood forecasting in data scarce regions. At the current state-of-art, these products cannot be used in the raw form for flood forecasting, even at smaller lead times. In the current study, these precipitation products are bias corrected using statistical techniques, such as additive and multiplicative bias corrections, and wavelet multi-resolution analysis (MRA) with India Meteorological Department (IMD) gridded precipitation product,obtained from gauge-based rainfall estimates. Neural network based rainfall-runoff modeling using these bias corrected products provide encouraging results for flood forecasting upto 48 hours lead time. We will present various statistical and graphical interpretations of catchment response to high rainfall events using both the raw and bias corrected precipitation products at different lead times.
Biased limiter experiments on text
International Nuclear Information System (INIS)
Phillips, P.E.; Wootton, A.J.; Rowan, W.L.; Ritz, C.P.; Rhodes, T.L.; Bengtson, R.D.; Hodge, W.L.; Durst, R.D.; McCool, S.C.; Richards, B.; Gentle, K.W.; Schoch, P.; Forster, J.C.; Hickok, R.L.; Evans, T.E.
1987-01-01
Experiments using an electrically biased limiter have been performed on the Texas Experimental Tokamak (TEXT). A small movable limiter is inserted past the main poloidal ring limiter (which is electrically connected to the vacuum vessel) and biased at V Lim with respect to it. The floating potential, plasma potential and shear layer position can be controlled. With vertical strokeV Lim vertical stroke ≥ 50 V the plasma density increases. For V Lim Lim > 0 the results obtained are inconclusive. Variation of V Lim changes the electrostatic turbulence which may explain the observed total flux changes. (orig.)
Indian Academy of Sciences (India)
Administrator
Journal of Genetics, Vol. 83, No. 2, August 2004. Keywords. codon bias; alcohol dehydrogenase; Darwinian ... RESEARCH COMMENTARY. Benefits of being biased! SUTIRTH DEY*. Evolutionary Biology Laboratory, Evolutionary & Organismal Biology Unit,. Jawaharlal Nehru Centre for Advanced Scientific Research,.
Hybrid biasing approaches for global variance reduction
International Nuclear Information System (INIS)
Wu, Zeyun; Abdel-Khalik, Hany S.
2013-01-01
A new variant of Monte Carlo—deterministic (DT) hybrid variance reduction approach based on Gaussian process theory is presented for accelerating convergence of Monte Carlo simulation and compared with Forward-Weighted Consistent Adjoint Driven Importance Sampling (FW-CADIS) approach implemented in the SCALE package from Oak Ridge National Laboratory. The new approach, denoted the Gaussian process approach, treats the responses of interest as normally distributed random processes. The Gaussian process approach improves the selection of the weight windows of simulated particles by identifying a subspace that captures the dominant sources of statistical response variations. Like the FW-CADIS approach, the Gaussian process approach utilizes particle importance maps obtained from deterministic adjoint models to derive weight window biasing. In contrast to the FW-CADIS approach, the Gaussian process approach identifies the response correlations (via a covariance matrix) and employs them to reduce the computational overhead required for global variance reduction (GVR) purpose. The effective rank of the covariance matrix identifies the minimum number of uncorrelated pseudo responses, which are employed to bias simulated particles. Numerical experiments, serving as a proof of principle, are presented to compare the Gaussian process and FW-CADIS approaches in terms of the global reduction in standard deviation of the estimated responses. - Highlights: ► Hybrid Monte Carlo Deterministic Method based on Gaussian Process Model is introduced. ► Method employs deterministic model to calculate responses correlations. ► Method employs correlations to bias Monte Carlo transport. ► Method compared to FW-CADIS methodology in SCALE code. ► An order of magnitude speed up is achieved for a PWR core model.
Directory of Open Access Journals (Sweden)
David Herrera
Full Text Available In two-alternative discrimination tasks, experimenters usually randomize the location of the rewarded stimulus so that systematic behavior with respect to irrelevant stimuli can only produce chance performance on the learning curves. One way to achieve this is to use random numbers derived from a discrete binomial distribution to create a 'full random training schedule' (FRS. When using FRS, however, sporadic but long laterally-biased training sequences occur by chance and such 'input biases' are thought to promote the generation of laterally-biased choices (i.e., 'output biases'. As an alternative, a 'Gellerman-like training schedule' (GLS can be used. It removes most input biases by prohibiting the reward from appearing on the same location for more than three consecutive trials. The sequence of past rewards obtained from choosing a particular discriminative stimulus influences the probability of choosing that same stimulus on subsequent trials. Assuming that the long-term average ratio of choices matches the long-term average ratio of reinforcers, we hypothesized that a reduced amount of input biases in GLS compared to FRS should lead to a reduced production of output biases. We compared the choice patterns produced by a 'Rational Decision Maker' (RDM in response to computer-generated FRS and GLS training sequences. To create a virtual RDM, we implemented an algorithm that generated choices based on past rewards. Our simulations revealed that, although the GLS presented fewer input biases than the FRS, the virtual RDM produced more output biases with GLS than with FRS under a variety of test conditions. Our results reveal that the statistical and temporal properties of training sequences interacted with the RDM to influence the production of output biases. Thus, discrete changes in the training paradigms did not translate linearly into modifications in the pattern of choices generated by a RDM. Virtual RDMs could be further employed to guide
Herrera, David; Treviño, Mario
2015-01-01
In two-alternative discrimination tasks, experimenters usually randomize the location of the rewarded stimulus so that systematic behavior with respect to irrelevant stimuli can only produce chance performance on the learning curves. One way to achieve this is to use random numbers derived from a discrete binomial distribution to create a 'full random training schedule' (FRS). When using FRS, however, sporadic but long laterally-biased training sequences occur by chance and such 'input biases' are thought to promote the generation of laterally-biased choices (i.e., 'output biases'). As an alternative, a 'Gellerman-like training schedule' (GLS) can be used. It removes most input biases by prohibiting the reward from appearing on the same location for more than three consecutive trials. The sequence of past rewards obtained from choosing a particular discriminative stimulus influences the probability of choosing that same stimulus on subsequent trials. Assuming that the long-term average ratio of choices matches the long-term average ratio of reinforcers, we hypothesized that a reduced amount of input biases in GLS compared to FRS should lead to a reduced production of output biases. We compared the choice patterns produced by a 'Rational Decision Maker' (RDM) in response to computer-generated FRS and GLS training sequences. To create a virtual RDM, we implemented an algorithm that generated choices based on past rewards. Our simulations revealed that, although the GLS presented fewer input biases than the FRS, the virtual RDM produced more output biases with GLS than with FRS under a variety of test conditions. Our results reveal that the statistical and temporal properties of training sequences interacted with the RDM to influence the production of output biases. Thus, discrete changes in the training paradigms did not translate linearly into modifications in the pattern of choices generated by a RDM. Virtual RDMs could be further employed to guide the selection of
Apparatus bias and place conditioning with ethanol in mice.
Cunningham, Christopher L; Ferree, Nikole K; Howard, MacKenzie A
2003-12-01
Although the distinction between "biased" and "unbiased" is generally recognized as an important methodological issue in place conditioning, previous studies have not adequately addressed the distinction between a biased/unbiased apparatus and a biased/unbiased stimulus assignment procedure. Moreover, a review of the recent literature indicates that many reports (70% of 76 papers published in 2001) fail to provide adequate information about apparatus bias. This issue is important because the mechanisms underlying a drug's effect in the place-conditioning procedure may differ depending on whether the apparatus is biased or unbiased. The present studies were designed to assess the impact of apparatus bias and stimulus assignment procedure on ethanol-induced place conditioning in mice (DBA/2 J). A secondary goal was to compare various dependent variables commonly used to index conditioned place preference. Apparatus bias was manipulated by varying the combination of tactile (floor) cues available during preference tests. Experiment 1 used an unbiased apparatus in which the stimulus alternatives were equally preferred during a pre-test as indicated by the group average. Experiment 2 used a biased apparatus in which one of the stimuli was strongly preferred by most mice (mean % time on cue = 67%) during the pre-test. In both studies, the stimulus paired with drug (CS+) was assigned randomly (i.e., an "unbiased" stimulus assignment procedure). Experimental mice received four pairings of CS+ with ethanol (2 g/kg, i.p.) and four pairings of the alternative stimulus (CS-) with saline; control mice received saline on both types of trial. Each experiment concluded with a 60-min choice test. With the unbiased apparatus (experiment 1), significant place conditioning was obtained regardless of whether drug was paired with the subject's initially preferred or non-preferred stimulus. However, with the biased apparatus (experiment 2), place conditioning was apparent only when
Directory of Open Access Journals (Sweden)
Chul Chung
2007-12-01
Full Text Available We estimate the CPI bias in Korea by employing the approach of Engel’s Law as suggested by Hamilton (2001. This paper is the first attempt to estimate the bias using Korean panel data, Korean Labor and Income Panel Study(KLIPS. Following Hamilton’s model with nonlinear specification correction, our estimation result shows that the cumulative CPI bias over the sample period (2000-2005 was 0.7 percent annually. This CPI bias implies that about 21 percent of the inflation rate during the period can be attributed to the bias. In light of purchasing power parity, we provide an interpretation of the estimated bias.
Bias correction of daily satellite precipitation data using genetic algorithm
Pratama, A. W.; Buono, A.; Hidayat, R.; Harsa, H.
2018-05-01
Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) was producted by blending Satellite-only Climate Hazards Group InfraRed Precipitation (CHIRP) with Stasion observations data. The blending process was aimed to reduce bias of CHIRP. However, Biases of CHIRPS on statistical moment and quantil values were high during wet season over Java Island. This paper presented a bias correction scheme to adjust statistical moment of CHIRP using observation precipitation data. The scheme combined Genetic Algorithm and Nonlinear Power Transformation, the results was evaluated based on different season and different elevation level. The experiment results revealed that the scheme robustly reduced bias on variance around 100% reduction and leaded to reduction of first, and second quantile biases. However, bias on third quantile only reduced during dry months. Based on different level of elevation, the performance of bias correction process is only significantly different on skewness indicators.
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
Quality assurance and statistical control
DEFF Research Database (Denmark)
Heydorn, K.
1991-01-01
In scientific research laboratories it is rarely possible to use quality assurance schemes, developed for large-scale analysis. Instead methods have been developed to control the quality of modest numbers of analytical results by relying on statistical control: Analysis of precision serves...... to detect analytical errors by comparing the a priori precision of the analytical results with the actual variability observed among replicates or duplicates. The method relies on the chi-square distribution to detect excess variability and is quite sensitive even for 5-10 results. Interference control...... serves to detect analytical bias by comparing results obtained by two different analytical methods, each relying on a different detection principle and therefore exhibiting different influence from matrix elements; only 5-10 sets of results are required to establish whether a regression line passes...
Truncated States Obtained by Iteration
International Nuclear Information System (INIS)
Cardoso, W. B.; Almeida, N. G. de
2008-01-01
We introduce the concept of truncated states obtained via iterative processes (TSI) and study its statistical features, making an analogy with dynamical systems theory (DST). As a specific example, we have studied TSI for the doubling and the logistic functions, which are standard functions in studying chaos. TSI for both the doubling and logistic functions exhibit certain similar patterns when their statistical features are compared from the point of view of DST
Directory of Open Access Journals (Sweden)
Mahmoud Moradi
2013-04-01
Full Text Available Most economic and finance theories are based on the assumption that during economic decision making, people would act totally rational and consider all available information. Nevertheless, behavioral finance focuses on studying of the role of psychological factors on economic participants’ behavior. The study shows that in real-world environment, people are influenced by emotional and cognitive errors and may make irrational financial decisions. In many cases, the participants of financial markets are not aware of their talents for error in decision making, so they are dissatisfied with their investments by considering some behavioral biases decisions. These decisions may often yield undesirable outcomes, which could influence economy, significantly. This paper presents a survey on the relationship between personality dimensions with behavioral biases and availability bias among investment managers in the Tehran Stock Exchange using SPSS software, descriptive and inferential statistics. The necessary data are collected through questionnaire and they are analyzed using some statistical tests. The preliminary results indicate that there is a relationship between personality dimensions and behavioral biases like conservatism bias and availability bias among the investors in the Tehran Stock Exchange.
International Nuclear Information System (INIS)
Blanchard, R.J.
1995-01-01
This documents Phase 1 determinations on sampler induced bias for four sampler types used in tank characterization. Each sampler, grab sampler or bottle-on-a-string, auger sampler, sludge sampler and universal sampler, is briefly discussed and their physical limits noted. Phase 2 of this document will define additional testing and analysis to further define Sampler Bias
2018-02-01
Department of the Army position unless so designated by other authorized documents. Citation of manufacturer’s or trade names does not constitute an... Interior view of the photovoltaic bias generator showing wrapped-wire side of circuit board...3 Fig. 4 Interior view of the photovoltaic bias generator showing component side of circuit board
Das-Smaal, E.A.
1990-01-01
On what grounds can we conclude that an act of categorization is biased? In this chapter, it is contended that in the absence of objective norms of what categories actually are, biases in categorization can only be specified in relation to theoretical understandings of categorization. Therefore, the
Approximate Bias Correction in Econometrics
James G. MacKinnon; Anthony A. Smith Jr.
1995-01-01
This paper discusses ways to reduce the bias of consistent estimators that are biased in finite samples. It is necessary that the bias function, which relates parameter values to bias, should be estimable by computer simulation or by some other method. If so, bias can be reduced or, in some cases that may not be unrealistic, even eliminated. In general, several evaluations of the bias function will be required to do this. Unfortunately, reducing bias may increase the variance, or even the mea...
Monte Carlo shielding analyses using an automated biasing procedure
International Nuclear Information System (INIS)
Tang, J.S.; Hoffman, T.J.
1988-01-01
A systematic and automated approach for biasing Monte Carlo shielding calculations is described. In particular, adjoint fluxes from a one-dimensional discrete ordinates calculation are used to generate biasing parameters for a Monte Carlo calculation. The entire procedure of adjoint calculation, biasing parameters generation, and Monte Carlo calculation has been automated. The automated biasing procedure has been applied to several realistic deep-penetration shipping cask problems. The results obtained for neutron and gamma-ray transport indicate that with the automated biasing procedure Monte Carlo shielding calculations of spent-fuel casks can be easily performed with minimum effort and that accurate results can be obtained at reasonable computing cost
Galaxy bias and primordial non-Gaussianity
Energy Technology Data Exchange (ETDEWEB)
Assassi, Valentin; Baumann, Daniel [DAMTP, Cambridge University, Wilberforce Road, Cambridge CB3 0WA (United Kingdom); Schmidt, Fabian, E-mail: assassi@ias.edu, E-mail: D.D.Baumann@uva.nl, E-mail: fabians@MPA-Garching.MPG.DE [Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, 85748 Garching (Germany)
2015-12-01
We present a systematic study of galaxy biasing in the presence of primordial non-Gaussianity. For a large class of non-Gaussian initial conditions, we define a general bias expansion and prove that it is closed under renormalization, thereby showing that the basis of operators in the expansion is complete. We then study the effects of primordial non-Gaussianity on the statistics of galaxies. We show that the equivalence principle enforces a relation between the scale-dependent bias in the galaxy power spectrum and that in the dipolar part of the bispectrum. This provides a powerful consistency check to confirm the primordial origin of any observed scale-dependent bias. Finally, we also discuss the imprints of anisotropic non-Gaussianity as motivated by recent studies of higher-spin fields during inflation.
Galaxy bias and primordial non-Gaussianity
International Nuclear Information System (INIS)
Assassi, Valentin; Baumann, Daniel; Schmidt, Fabian
2015-01-01
We present a systematic study of galaxy biasing in the presence of primordial non-Gaussianity. For a large class of non-Gaussian initial conditions, we define a general bias expansion and prove that it is closed under renormalization, thereby showing that the basis of operators in the expansion is complete. We then study the effects of primordial non-Gaussianity on the statistics of galaxies. We show that the equivalence principle enforces a relation between the scale-dependent bias in the galaxy power spectrum and that in the dipolar part of the bispectrum. This provides a powerful consistency check to confirm the primordial origin of any observed scale-dependent bias. Finally, we also discuss the imprints of anisotropic non-Gaussianity as motivated by recent studies of higher-spin fields during inflation
... 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 ...
DEFF Research Database (Denmark)
Drecourt, J.-P.; Madsen, H.; Rosbjerg, Dan
2006-01-01
This paper reviews two different approaches that have been proposed to tackle the problems of model bias with the Kalman filter: the use of a colored noise model and the implementation of a separate bias filter. Both filters are implemented with and without feedback of the bias into the model state....... The colored noise filter formulation is extended to correct both time correlated and uncorrelated model error components. A more stable version of the separate filter without feedback is presented. The filters are implemented in an ensemble framework using Latin hypercube sampling. The techniques...... are illustrated on a simple one-dimensional groundwater problem. The results show that the presented filters outperform the standard Kalman filter and that the implementations with bias feedback work in more general conditions than the implementations without feedback. 2005 Elsevier Ltd. All rights reserved....
Directory of Open Access Journals (Sweden)
James Sundali
2006-07-01
Full Text Available We examine two departures of individual perceptions of randomness from probability theory: the hot hand and the gambler's fallacy, and their respective opposites. This paper's first contribution is to use data from the field (individuals playing roulette in a casino to demonstrate the existence and impact of these biases that have been previously documented in the lab. Decisions in the field are consistent with biased beliefs, although we observe significant individual heterogeneity in the population. A second contribution is to separately identify these biases within a given individual, then to examine their within-person correlation. We find a positive and significant correlation across individuals between hot hand and gambler's fallacy biases, suggesting a common (root cause of the two related errors. We speculate as to the source of this correlation (locus of control, and suggest future research which could test this speculation.
Introduction to Unconscious Bias
Schmelz, Joan T.
2010-05-01
We all have biases, and we are (for the most part) unaware of them. In general, men and women BOTH unconsciously devalue the contributions of women. This can have a detrimental effect on grant proposals, job applications, and performance reviews. Sociology is way ahead of astronomy in these studies. When evaluating identical application packages, male and female University psychology professors preferred 2:1 to hire "Brian” over "Karen” as an assistant professor. When evaluating a more experienced record (at the point of promotion to tenure), reservations were expressed four times more often when the name was female. This unconscious bias has a repeated negative effect on Karen's career. This talk will introduce the concept of unconscious bias and also give recommendations on how to address it using an example for a faculty search committee. The process of eliminating unconscious bias begins with awareness, then moves to policy and practice, and ends with accountability.
Anil V. Mishra; Umaru B. Conteh
2014-01-01
This paper constructs the float adjusted measure of home bias and explores the determinants of bond home bias by employing the International Monetary Fund's high quality dataset (2001 to 2009) on cross-border bond investment. The paper finds that Australian investors' prefer investing in countries with higher economic development and more developed bond markets. Exchange rate volatility appears to be an impediment for cross-border bond investment. Investors prefer investing in countries with ...
Pointwise probability reinforcements for robust statistical inference.
Frénay, Benoît; Verleysen, Michel
2014-02-01
Statistical inference using machine learning techniques may be difficult with small datasets because of abnormally frequent data (AFDs). AFDs are observations that are much more frequent in the training sample that they should be, with respect to their theoretical probability, and include e.g. outliers. Estimates of parameters tend to be biased towards models which support such data. This paper proposes to introduce pointwise probability reinforcements (PPRs): the probability of each observation is reinforced by a PPR and a regularisation allows controlling the amount of reinforcement which compensates for AFDs. The proposed solution is very generic, since it can be used to robustify any statistical inference method which can be formulated as a likelihood maximisation. Experiments show that PPRs can be easily used to tackle regression, classification and projection: models are freed from the influence of outliers. Moreover, outliers can be filtered manually since an abnormality degree is obtained for each observation. Copyright © 2013 Elsevier Ltd. All rights reserved.
Podsakoff, Philip M; MacKenzie, Scott B; Lee, Jeong-Yeon; Podsakoff, Nathan P
2003-10-01
Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.
DEFF Research Database (Denmark)
Jensen, Henning Tarp; Robinson, Sherman; Tarp, Finn
The measurement issue is the key issue in the literature on trade policy-induced agri-cultural price incentive bias. This paper introduces a general equilibrium effective rate of protection (GE-ERP) measure, which extends and generalizes earlier partial equilibrium nominal protection measures...... shares and intersectoral linkages - are crucial for determining the sign and magnitude of trade policy bias. The GE-ERP measure is therefore uniquely suited to capture the full impact of trade policies on agricultural price incentives. A Monte Carlo procedure confirms that the results are robust....... For the 15 sample countries, the results indicate that the agricultural price incentive bias, which was generally perceived to exist during the 1980s, was largely eliminated during the 1990s. The results also demonstrate that general equilibrium effects and country-specific characteristics - including trade...
... 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 ...
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.
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
Forster, Malcolm R
2011-01-01
Statisticians and philosophers of science have many common interests but restricted communication with each other. This volume aims to remedy these shortcomings. It provides state-of-the-art research in the area of philosophy of statistics by encouraging numerous experts to communicate with one another without feeling "restricted” by their disciplines or thinking "piecemeal” in their treatment of issues. A second goal of this book is to present work in the field without bias toward any particular statistical paradigm. Broadly speaking, the essays in this Handbook are concerned with problems of induction, statistics and probability. For centuries, foundational problems like induction have been among philosophers' favorite topics; recently, however, non-philosophers have increasingly taken a keen interest in these issues. This volume accordingly contains papers by both philosophers and non-philosophers, including scholars from nine academic disciplines.
Measuring agricultural policy bias
DEFF Research Database (Denmark)
Jensen, Henning Tarp; Robinson, Sherman; Tarp, Finn
2010-01-01
Measurement is a key issue in the literature on price incentive bias induced by trade policy. We introduce a general equilibrium measure of the relative effective rate of protection, which generalizes earlier protection measures. For our fifteen sample countries, results indicate that the agricul...
Khusenov, Arslonnazar; Rakhmanberdiev, Gappar; Rakhimov, Dilshod; Khalikov, Muzaffar
2014-01-01
In the article first obtained inulin ester inulin acetate, by etherification of inulin with acetic anhydride has been exposed. Obtained product has been studied using elementary analysis and IR spectroscopy.
Empirical single sample quantification of bias and variance in Q-ball imaging.
Hainline, Allison E; Nath, Vishwesh; Parvathaneni, Prasanna; Blaber, Justin A; Schilling, Kurt G; Anderson, Adam W; Kang, Hakmook; Landman, Bennett A
2018-02-06
The bias and variance of high angular resolution diffusion imaging methods have not been thoroughly explored in the literature and may benefit from the simulation extrapolation (SIMEX) and bootstrap techniques to estimate bias and variance of high angular resolution diffusion imaging metrics. The SIMEX approach is well established in the statistics literature and uses simulation of increasingly noisy data to extrapolate back to a hypothetical case with no noise. The bias of calculated metrics can then be computed by subtracting the SIMEX estimate from the original pointwise measurement. The SIMEX technique has been studied in the context of diffusion imaging to accurately capture the bias in fractional anisotropy measurements in DTI. Herein, we extend the application of SIMEX and bootstrap approaches to characterize bias and variance in metrics obtained from a Q-ball imaging reconstruction of high angular resolution diffusion imaging data. The results demonstrate that SIMEX and bootstrap approaches provide consistent estimates of the bias and variance of generalized fractional anisotropy, respectively. The RMSE for the generalized fractional anisotropy estimates shows a 7% decrease in white matter and an 8% decrease in gray matter when compared with the observed generalized fractional anisotropy estimates. On average, the bootstrap technique results in SD estimates that are approximately 97% of the true variation in white matter, and 86% in gray matter. Both SIMEX and bootstrap methods are flexible, estimate population characteristics based on single scans, and may be extended for bias and variance estimation on a variety of high angular resolution diffusion imaging metrics. © 2018 International Society for Magnetic Resonance in Medicine.
Department of Homeland Security — Accident statistics available on the Coast Guard’s website by state, year, and one variable to obtain tables and/or graphs. Data from reports has been loaded for...
Energy Technology Data Exchange (ETDEWEB)
Cunha, Carlos E. [KIPAC, Menlo Park; Huterer, Dragan [Michigan U.; Lin, Huan [Fermilab; Busha, Michael T. [Zurich U.; Wechsler, Risa H. [SLAC
2014-10-11
We use N-body-spectro-photometric simulations to investigate the impact of incompleteness and incorrect redshifts in spectroscopic surveys to photometric redshift training and calibration and the resulting effects on cosmological parameter estimation from weak lensing shear-shear correlations. The photometry of the simulations is modeled after the upcoming Dark Energy Survey and the spectroscopy is based on a low/intermediate resolution spectrograph with wavelength coverage of 5500{\\AA} < {\\lambda} < 9500{\\AA}. The principal systematic errors that such a spectroscopic follow-up encounters are incompleteness (inability to obtain spectroscopic redshifts for certain galaxies) and wrong redshifts. Encouragingly, we find that a neural network-based approach can effectively describe the spectroscopic incompleteness in terms of the galaxies' colors, so that the spectroscopic selection can be applied to the photometric sample. Hence, we find that spectroscopic incompleteness yields no appreciable biases to cosmology, although the statistical constraints degrade somewhat because the photometric survey has to be culled to match the spectroscopic selection. Unfortunately, wrong redshifts have a more severe impact: the cosmological biases are intolerable if more than a percent of the spectroscopic redshifts are incorrect. Moreover, we find that incorrect redshifts can also substantially degrade the accuracy of training set based photo-z estimators. The main problem is the difficulty of obtaining redshifts, either spectroscopically or photometrically, for objects at z > 1.3. We discuss several approaches for reducing the cosmological biases, in particular finding that photo-z error estimators can reduce biases appreciably.
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...
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.
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
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.
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.
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
... Testing Treatment & Outcomes Health Professionals Statistics More Resources Candidiasis Candida infections of the mouth, throat, and esophagus Vaginal candidiasis Invasive candidiasis Definition Symptoms Risk & Prevention Sources Diagnosis ...
Biases in Visual, Auditory, and Audiovisual Perception of Space.
Directory of Open Access Journals (Sweden)
Brian Odegaard
2015-12-01
Full Text Available Localization of objects and events in the environment is critical for survival, as many perceptual and motor tasks rely on estimation of spatial location. Therefore, it seems reasonable to assume that spatial localizations should generally be accurate. Curiously, some previous studies have reported biases in visual and auditory localizations, but these studies have used small sample sizes and the results have been mixed. Therefore, it is not clear (1 if the reported biases in localization responses are real (or due to outliers, sampling bias, or other factors, and (2 whether these putative biases reflect a bias in sensory representations of space or a priori expectations (which may be due to the experimental setup, instructions, or distribution of stimuli. Here, to address these questions, a dataset of unprecedented size (obtained from 384 observers was analyzed to examine presence, direction, and magnitude of sensory biases, and quantitative computational modeling was used to probe the underlying mechanism(s driving these effects. Data revealed that, on average, observers were biased towards the center when localizing visual stimuli, and biased towards the periphery when localizing auditory stimuli. Moreover, quantitative analysis using a Bayesian Causal Inference framework suggests that while pre-existing spatial biases for central locations exert some influence, biases in the sensory representations of both visual and auditory space are necessary to fully explain the behavioral data. How are these opposing visual and auditory biases reconciled in conditions in which both auditory and visual stimuli are produced by a single event? Potentially, the bias in one modality could dominate, or the biases could interact/cancel out. The data revealed that when integration occurred in these conditions, the visual bias dominated, but the magnitude of this bias was reduced compared to unisensory conditions. Therefore, multisensory integration not only
Biases in Visual, Auditory, and Audiovisual Perception of Space
Odegaard, Brian; Wozny, David R.; Shams, Ladan
2015-01-01
Localization of objects and events in the environment is critical for survival, as many perceptual and motor tasks rely on estimation of spatial location. Therefore, it seems reasonable to assume that spatial localizations should generally be accurate. Curiously, some previous studies have reported biases in visual and auditory localizations, but these studies have used small sample sizes and the results have been mixed. Therefore, it is not clear (1) if the reported biases in localization responses are real (or due to outliers, sampling bias, or other factors), and (2) whether these putative biases reflect a bias in sensory representations of space or a priori expectations (which may be due to the experimental setup, instructions, or distribution of stimuli). Here, to address these questions, a dataset of unprecedented size (obtained from 384 observers) was analyzed to examine presence, direction, and magnitude of sensory biases, and quantitative computational modeling was used to probe the underlying mechanism(s) driving these effects. Data revealed that, on average, observers were biased towards the center when localizing visual stimuli, and biased towards the periphery when localizing auditory stimuli. Moreover, quantitative analysis using a Bayesian Causal Inference framework suggests that while pre-existing spatial biases for central locations exert some influence, biases in the sensory representations of both visual and auditory space are necessary to fully explain the behavioral data. How are these opposing visual and auditory biases reconciled in conditions in which both auditory and visual stimuli are produced by a single event? Potentially, the bias in one modality could dominate, or the biases could interact/cancel out. The data revealed that when integration occurred in these conditions, the visual bias dominated, but the magnitude of this bias was reduced compared to unisensory conditions. Therefore, multisensory integration not only improves the
Lash, Timothy L
2007-11-26
The associations of pesticide exposure with disease outcomes are estimated without the benefit of a randomized design. For this reason and others, these studies are susceptible to systematic errors. I analyzed studies of the associations between alachlor and glyphosate exposure and cancer incidence, both derived from the Agricultural Health Study cohort, to quantify the bias and uncertainty potentially attributable to systematic error. For each study, I identified the prominent result and important sources of systematic error that might affect it. I assigned probability distributions to the bias parameters that allow quantification of the bias, drew a value at random from each assigned distribution, and calculated the estimate of effect adjusted for the biases. By repeating the draw and adjustment process over multiple iterations, I generated a frequency distribution of adjusted results, from which I obtained a point estimate and simulation interval. These methods were applied without access to the primary record-level dataset. The conventional estimates of effect associating alachlor and glyphosate exposure with cancer incidence were likely biased away from the null and understated the uncertainty by quantifying only random error. For example, the conventional p-value for a test of trend in the alachlor study equaled 0.02, whereas fewer than 20% of the bias analysis iterations yielded a p-value of 0.02 or lower. Similarly, the conventional fully-adjusted result associating glyphosate exposure with multiple myleoma equaled 2.6 with 95% confidence interval of 0.7 to 9.4. The frequency distribution generated by the bias analysis yielded a median hazard ratio equal to 1.5 with 95% simulation interval of 0.4 to 8.9, which was 66% wider than the conventional interval. Bias analysis provides a more complete picture of true uncertainty than conventional frequentist statistical analysis accompanied by a qualitative description of study limitations. The latter approach is
Directory of Open Access Journals (Sweden)
Lash Timothy L
2007-11-01
Full Text Available Abstract Background The associations of pesticide exposure with disease outcomes are estimated without the benefit of a randomized design. For this reason and others, these studies are susceptible to systematic errors. I analyzed studies of the associations between alachlor and glyphosate exposure and cancer incidence, both derived from the Agricultural Health Study cohort, to quantify the bias and uncertainty potentially attributable to systematic error. Methods For each study, I identified the prominent result and important sources of systematic error that might affect it. I assigned probability distributions to the bias parameters that allow quantification of the bias, drew a value at random from each assigned distribution, and calculated the estimate of effect adjusted for the biases. By repeating the draw and adjustment process over multiple iterations, I generated a frequency distribution of adjusted results, from which I obtained a point estimate and simulation interval. These methods were applied without access to the primary record-level dataset. Results The conventional estimates of effect associating alachlor and glyphosate exposure with cancer incidence were likely biased away from the null and understated the uncertainty by quantifying only random error. For example, the conventional p-value for a test of trend in the alachlor study equaled 0.02, whereas fewer than 20% of the bias analysis iterations yielded a p-value of 0.02 or lower. Similarly, the conventional fully-adjusted result associating glyphosate exposure with multiple myleoma equaled 2.6 with 95% confidence interval of 0.7 to 9.4. The frequency distribution generated by the bias analysis yielded a median hazard ratio equal to 1.5 with 95% simulation interval of 0.4 to 8.9, which was 66% wider than the conventional interval. Conclusion Bias analysis provides a more complete picture of true uncertainty than conventional frequentist statistical analysis accompanied by a
Estimation bias and bias correction in reduced rank autoregressions
DEFF Research Database (Denmark)
Nielsen, Heino Bohn
2017-01-01
This paper characterizes the finite-sample bias of the maximum likelihood estimator (MLE) in a reduced rank vector autoregression and suggests two simulation-based bias corrections. One is a simple bootstrap implementation that approximates the bias at the MLE. The other is an iterative root...
Petocz, Peter; Sowey, Eric
2012-01-01
The term "data snooping" refers to the practice of choosing which statistical analyses to apply to a set of data after having first looked at those data. Data snooping contradicts a fundamental precept of applied statistics, that the scheme of analysis is to be planned in advance. In this column, the authors shall elucidate the…
Petocz, Peter; Sowey, Eric
2008-01-01
In this article, the authors focus on hypothesis testing--that peculiarly statistical way of deciding things. Statistical methods for testing hypotheses were developed in the 1920s and 1930s by some of the most famous statisticians, in particular Ronald Fisher, Jerzy Neyman and Egon Pearson, who laid the foundations of almost all modern methods of…
Glaz, Joseph
2009-01-01
Suitable for graduate students and researchers in applied probability and statistics, as well as for scientists in biology, computer science, pharmaceutical science and medicine, this title brings together a collection of chapters illustrating the depth and diversity of theory, methods and applications in the area of scan statistics.
Lyons, L.
2016-01-01
Accelerators and detectors are expensive, both in terms of money and human effort. It is thus important to invest effort in performing a good statistical anal- ysis of the data, in order to extract the best information from it. This series of five lectures deals with practical aspects of statistical issues that arise in typical High Energy Physics analyses.
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.
Thermodynamics for Fractal Statistics
da Cruz, Wellington
1998-01-01
We consider for an anyon gas its termodynamics properties taking into account the fractal statistics obtained by us recently. This approach describes the anyonic excitations in terms of equivalence classes labeled by fractal parameter or Hausdorff dimension $h$. An exact equation of state is obtained in the high-temperature and low-temperature limits, for gases with a constant density of states.
Statistical theory and inference
Olive, David J
2014-01-01
This text is for a one semester graduate course in statistical theory and covers minimal and complete sufficient statistics, maximum likelihood estimators, method of moments, bias and mean square error, uniform minimum variance estimators and the Cramer-Rao lower bound, an introduction to large sample theory, likelihood ratio tests and uniformly most powerful tests and the Neyman Pearson Lemma. A major goal of this text is to make these topics much more accessible to students by using the theory of exponential families. Exponential families, indicator functions and the support of the distribution are used throughout the text to simplify the theory. More than 50 ``brand name" distributions are used to illustrate the theory with many examples of exponential families, maximum likelihood estimators and uniformly minimum variance unbiased estimators. There are many homework problems with over 30 pages of solutions.
The Bias of the Gini Coefficient due to Grouping
T.G.M. van Ourti (Tom); Ph. Clarke (Philip)
2008-01-01
textabstractWe propose a first order bias correction term for the Gini index to reduce the bias due to grouping. The first order correction term is obtained from studying the estimator of the Gini index within a measurement error framework. In addition, it reveals an intuitive formula for the
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
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
Feiveson, Alan H.; Foy, Millennia; Ploutz-Snyder, Robert; Fiedler, James
2014-01-01
Do you have elevated p-values? Is the data analysis process getting you down? Do you experience anxiety when you need to respond to criticism of statistical methods in your manuscript? You may be suffering from Insufficient Statistical Support Syndrome (ISSS). For symptomatic relief of ISSS, come for a free consultation with JSC biostatisticians at our help desk during the poster sessions at the HRP Investigators Workshop. Get answers to common questions about sample size, missing data, multiple testing, when to trust the results of your analyses and more. Side effects may include sudden loss of statistics anxiety, improved interpretation of your data, and increased confidence in your results.
Effects of Model Chemistry and Data Biases on Stratospheric Ozone Assimilation
National Research Council Canada - National Science Library
Coy, L; Allen, D. R; Eckermann, S. D; McCormack, J. P; Stajner, I; Hogan, T. F
2007-01-01
.... In this study, O-F statistics from the Global Ozone Assimilation Testing System (GOATS) are used to examine how ozone assimilation products and their associated O-F statistics depend on input data biases and ozone photochemistry parameterizations (OPP...
Energy Technology Data Exchange (ETDEWEB)
Wendelberger, Laura Jean [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-08-08
In large datasets, it is time consuming or even impossible to pick out interesting images. Our proposed solution is to find statistics to quantify the information in each image and use those to identify and pick out images of interest.
U.S. Department of Health & Human Services — The CMS Center for Strategic Planning produces an annual CMS Statistics reference booklet that provides a quick reference for summary information about health...
Serdobolskii, Vadim Ivanovich
2007-01-01
This monograph presents mathematical theory of statistical models described by the essentially large number of unknown parameters, comparable with sample size but can also be much larger. In this meaning, the proposed theory can be called "essentially multiparametric". It is developed on the basis of the Kolmogorov asymptotic approach in which sample size increases along with the number of unknown parameters.This theory opens a way for solution of central problems of multivariate statistics, which up until now have not been solved. Traditional statistical methods based on the idea of an infinite sampling often break down in the solution of real problems, and, dependent on data, can be inefficient, unstable and even not applicable. In this situation, practical statisticians are forced to use various heuristic methods in the hope the will find a satisfactory solution.Mathematical theory developed in this book presents a regular technique for implementing new, more efficient versions of statistical procedures. ...
... Search Form Controls Cancel Submit Search the CDC Gonorrhea Note: Javascript is disabled or is not supported ... Twitter STD on Facebook Sexually Transmitted Diseases (STDs) Gonorrhea Statistics Recommend on Facebook Tweet Share Compartir Gonorrhea ...
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...
MacKenzie, Dana
2004-01-01
The drawbacks of using 19th-century mathematics in physics and astronomy are illustrated. To continue with the expansion of the knowledge about the cosmos, the scientists will have to come in terms with modern statistics. Some researchers have deliberately started importing techniques that are used in medical research. However, the physicists need to identify the brand of statistics that will be suitable for them, and make a choice between the Bayesian and the frequentists approach. (Edited abstract).
Obesity, the endocannabinoid system, and bias arising from pharmaceutical sponsorship.
McPartland, John M
2009-01-01
Previous research has shown that academic physicians conflicted by funding from the pharmaceutical industry have corrupted evidence based medicine and helped enlarge the market for drugs. Physicians made pharmaceutical-friendly statements, engaged in disease mongering, and signed biased review articles ghost-authored by corporate employees. This paper tested the hypothesis that bias affects review articles regarding rimonabant, an anti-obesity drug that blocks the central cannabinoid receptor. A MEDLINE search was performed for rimonabant review articles, limited to articles authored by USA physicians who served as consultants for the company that manufactures rimonabant. Extracted articles were examined for industry-friendly bias, identified by three methods: analysis with a validated instrument for monitoring bias in continuing medical education (CME); analysis for bias defined as statements that ran contrary to external evidence; and a tally of misrepresentations about the endocannabinoid system. Eight review articles were identified, but only three disclosed authors' financial conflicts of interest, despite easily accessible information to the contrary. The Takhar CME bias instrument demonstrated statistically significant bias in all the review articles. Biased statements that were nearly identical reappeared in the articles, including disease mongering, exaggerating rimonabant's efficacy and safety, lack of criticisms regarding rimonabant clinical trials, and speculations about surrogate markers stated as facts. Distinctive and identical misrepresentations regarding the endocannabinoid system also reappeared in articles by different authors. The findings are characteristic of bias that arises from financial conflicts of interest, and suggestive of ghostwriting by a common author. Resolutions for this scenario are proposed.
International Nuclear Information System (INIS)
Tylee, J.L.
1981-01-01
A method for detecting and identifying biases in the pressure and level sensors of a pressurized water reactor (PWR) pressurizer is described. The generalized likelihood ratio (GLR) technique performs statistical tests on the innovations sequence of a Kalman filter state estimator and is capable of determining when a bias appears, in what sensor the bias exists, and estimating the bias magnitude. Simulation results using a second-order linear, discrete PWR pressurizer model demonstrate the capabilities of the GLR method
Implementation of linear bias corrections for calorimeters at Mound
International Nuclear Information System (INIS)
Barnett, T.M.
1993-01-01
In the past, Mound has generally made relative bias corrections as part of the calibration of individual calorimeters. The correction made was the same over the entire operating range of the calorimeter, regardless of the magnitude of the range. Recently, an investigation was performed to check the relevancy of using linear bias corrections to calibrate the calorimeters. The bias is obtained by measuring calibrated plutonium and/or electrical heat standards over the operating range of the calorimeter. The bias correction is then calculated using a simple least squares fit (y = mx + b) of the bias in milliwatts over the operating range of the calorimeter in watts. The equation used is B i = B 0 + (B w * W m ), where B i is the bias at any given power in milliwatts, B 0 is the intercept (absolute bias in milliwatts), B w is the slope (relative bias in milliwatts per watt), and W m is the measured power in watts. The results of the study showed a decrease in the random error of bias corrected data for most of the calorimeters which are operated over a large wattage range (greater than an order of magnitude). The linear technique for bias correction has been fully implemented at Mound and has been included in the Technical Manual, ''A Measurement Control Program for Radiometric Calorimeters at Mound'' (MD-21900)
Generalized $L-, M-$, and $R$-Statistics
Serfling, Robert J.
1984-01-01
A class of statistics generalizing $U$-statistics and $L$-statistics, and containing other varieties of statistic as well, such as trimmed $U$-statistics, is studied. Using the differentiable statistical function approach, differential approximations are obtained and the influence curves of these generalized $L$-statistics are derived. These results are employed to establish asymptotic normality for such statistics. Parallel generalizations of $M$- and $R$-statistics are noted. Strong converg...
Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona
2018-01-01
Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.
Sampling of temporal networks: Methods and biases
Rocha, Luis E. C.; Masuda, Naoki; Holme, Petter
2017-11-01
Temporal networks have been increasingly used to model a diversity of systems that evolve in time; for example, human contact structures over which dynamic processes such as epidemics take place. A fundamental aspect of real-life networks is that they are sampled within temporal and spatial frames. Furthermore, one might wish to subsample networks to reduce their size for better visualization or to perform computationally intensive simulations. The sampling method may affect the network structure and thus caution is necessary to generalize results based on samples. In this paper, we study four sampling strategies applied to a variety of real-life temporal networks. We quantify the biases generated by each sampling strategy on a number of relevant statistics such as link activity, temporal paths and epidemic spread. We find that some biases are common in a variety of networks and statistics, but one strategy, uniform sampling of nodes, shows improved performance in most scenarios. Given the particularities of temporal network data and the variety of network structures, we recommend that the choice of sampling methods be problem oriented to minimize the potential biases for the specific research questions on hand. Our results help researchers to better design network data collection protocols and to understand the limitations of sampled temporal network data.
Goodman, J. W.
This book is based on the thesis that some training in the area of statistical optics should be included as a standard part of any advanced optics curriculum. Random variables are discussed, taking into account definitions of probability and random variables, distribution functions and density functions, an extension to two or more random variables, statistical averages, transformations of random variables, sums of real random variables, Gaussian random variables, complex-valued random variables, and random phasor sums. Other subjects examined are related to random processes, some first-order properties of light waves, the coherence of optical waves, some problems involving high-order coherence, effects of partial coherence on imaging systems, imaging in the presence of randomly inhomogeneous media, and fundamental limits in photoelectric detection of light. Attention is given to deterministic versus statistical phenomena and models, the Fourier transform, and the fourth-order moment of the spectrum of a detected speckle image.
Schwabl, Franz
2006-01-01
The completely revised new edition of the classical book on Statistical Mechanics covers the basic concepts of equilibrium and non-equilibrium statistical physics. In addition to a deductive approach to equilibrium statistics and thermodynamics based on a single hypothesis - the form of the microcanonical density matrix - this book treats the most important elements of non-equilibrium phenomena. Intermediate calculations are presented in complete detail. Problems at the end of each chapter help students to consolidate their understanding of the material. Beyond the fundamentals, this text demonstrates the breadth of the field and its great variety of applications. Modern areas such as renormalization group theory, percolation, stochastic equations of motion and their applications to critical dynamics, kinetic theories, as well as fundamental considerations of irreversibility, are discussed. The text will be useful for advanced students of physics and other natural sciences; a basic knowledge of quantum mechan...
Jana, Madhusudan
2015-01-01
Statistical mechanics is self sufficient, written in a lucid manner, keeping in mind the exam system of the universities. Need of study this subject and its relation to Thermodynamics is discussed in detail. Starting from Liouville theorem gradually, the Statistical Mechanics is developed thoroughly. All three types of Statistical distribution functions are derived separately with their periphery of applications and limitations. Non-interacting ideal Bose gas and Fermi gas are discussed thoroughly. Properties of Liquid He-II and the corresponding models have been depicted. White dwarfs and condensed matter physics, transport phenomenon - thermal and electrical conductivity, Hall effect, Magneto resistance, viscosity, diffusion, etc. are discussed. Basic understanding of Ising model is given to explain the phase transition. The book ends with a detailed coverage to the method of ensembles (namely Microcanonical, canonical and grand canonical) and their applications. Various numerical and conceptual problems ar...
Guénault, Tony
2007-01-01
In this revised and enlarged second edition of an established text Tony Guénault provides a clear and refreshingly readable introduction to statistical physics, an essential component of any first degree in physics. The treatment itself is self-contained and concentrates on an understanding of the physical ideas, without requiring a high level of mathematical sophistication. A straightforward quantum approach to statistical averaging is adopted from the outset (easier, the author believes, than the classical approach). The initial part of the book is geared towards explaining the equilibrium properties of a simple isolated assembly of particles. Thus, several important topics, for example an ideal spin-½ solid, can be discussed at an early stage. The treatment of gases gives full coverage to Maxwell-Boltzmann, Fermi-Dirac and Bose-Einstein statistics. Towards the end of the book the student is introduced to a wider viewpoint and new chapters are included on chemical thermodynamics, interactions in, for exam...
On biases in precise point positioning with multi-constellation and multi-frequency GNSS data
International Nuclear Information System (INIS)
El-Mowafy, A; Deo, M; Rizos, C
2016-01-01
Various types of biases in Global Navigation Satellite System (GNSS) data preclude integer ambiguity fixing and degrade solution accuracy when not being corrected during precise point positioning (PPP). In this contribution, these biases are first reviewed, including satellite and receiver hardware biases, differential code biases, differential phase biases, initial fractional phase biases, inter-system receiver time biases, and system time scale offset. PPP models that take account of these biases are presented for two cases using ionosphere-free observations. The first case is when using primary signals that are used to generate precise orbits and clock corrections. The second case applies when using additional signals to the primary ones. In both cases, measurements from single and multiple constellations are addressed. It is suggested that the satellite-related code biases be handled as calibrated quantities that are obtained from multi-GNSS experiment products and the fractional phase cycle biases obtained from a network to allow for integer ambiguity fixing. Some receiver-related biases are removed using between-satellite single differencing, whereas other receiver biases such as inter-system biases are lumped with differential code and phase biases and need to be estimated. The testing results show that the treatment of biases significantly improves solution convergence in the float ambiguity PPP mode, and leads to ambiguity-fixed PPP within a few minutes with a small improvement in solution precision. (paper)
Mandl, Franz
1988-01-01
The Manchester Physics Series General Editors: D. J. Sandiford; F. Mandl; A. C. Phillips Department of Physics and Astronomy, University of Manchester Properties of Matter B. H. Flowers and E. Mendoza Optics Second Edition F. G. Smith and J. H. Thomson Statistical Physics Second Edition E. Mandl Electromagnetism Second Edition I. S. Grant and W. R. Phillips Statistics R. J. Barlow Solid State Physics Second Edition J. R. Hook and H. E. Hall Quantum Mechanics F. Mandl Particle Physics Second Edition B. R. Martin and G. Shaw The Physics of Stars Second Edition A. C. Phillips Computing for Scient
Rohatgi, Vijay K
2003-01-01
Unified treatment of probability and statistics examines and analyzes the relationship between the two fields, exploring inferential issues. Numerous problems, examples, and diagrams--some with solutions--plus clear-cut, highlighted summaries of results. Advanced undergraduate to graduate level. Contents: 1. Introduction. 2. Probability Model. 3. Probability Distributions. 4. Introduction to Statistical Inference. 5. More on Mathematical Expectation. 6. Some Discrete Models. 7. Some Continuous Models. 8. Functions of Random Variables and Random Vectors. 9. Large-Sample Theory. 10. General Meth
Levine-Wissing, Robin
2012-01-01
All Access for the AP® Statistics Exam Book + Web + Mobile Everything you need to prepare for the Advanced Placement® exam, in a study system built around you! There are many different ways to prepare for an Advanced Placement® exam. What's best for you depends on how much time you have to study and how comfortable you are with the subject matter. To score your highest, you need a system that can be customized to fit you: your schedule, your learning style, and your current level of knowledge. This book, and the online tools that come with it, will help you personalize your AP® Statistics prep
Davidson, Norman
2003-01-01
Clear and readable, this fine text assists students in achieving a grasp of the techniques and limitations of statistical mechanics. The treatment follows a logical progression from elementary to advanced theories, with careful attention to detail and mathematical development, and is sufficiently rigorous for introductory or intermediate graduate courses.Beginning with a study of the statistical mechanics of ideal gases and other systems of non-interacting particles, the text develops the theory in detail and applies it to the study of chemical equilibrium and the calculation of the thermody
Bias and Causation Models and Judgment for Valid Comparisons
Weisberg, Herbert I
2010-01-01
A one-of-a-kind resource on identifying and dealing with bias in statistical research on causal effects. Do cell phones cause cancer? Can a new curriculum increase student achievement? Determining what the real causes of such problems are, and how powerful their effects may be, are central issues in research across various fields of study. Some researchers are highly skeptical of drawing causal conclusions except in tightly controlled randomized experiments, while others discount the threats posed by different sources of bias, even in less rigorous observational studies. Bias and Causation pre
Presence of bias in radiographer plain film reading performance studies
International Nuclear Information System (INIS)
Brealey, S.; Scally, A.J.; Thomas, N.B.
2002-01-01
Purpose To raise awareness of the frequency of bias that can affect the quality of radiographer plain film reading performance studies. Methods Studies that assessed radiographer(s) plain film reading performance were located by searching electronic databases and grey literature, hand-searching journals, personal communication and scanning reference lists. Thirty studies were judged eligible from all data sources. Results A one-way analysis of variance (ANOVA) demonstrates no statistically significant difference (P=0.25) in the mean proportion of biases present from diagnostic accuracy (0.37), performance (0.42) and outcome (0.44) study designs. Pearson's correlation coefficient showed no statistically significant linear association between the proportion of biases present for the three different study designs and the year that the study was performed. The frequency of biases in film and observer selection and application of the reference standard was quite low. In contrast, many biases were present concerning independence of film reporting and comparison of reports for concordance. Conclusions The findings indicate variation in the presence of bias in radiographer plain film reading performance studies. The careful consideration of bias is an essential component of study quality and hence the validity of the evidence-base used to underpin radiographic reporting policy
International Nuclear Information System (INIS)
Kiwi, Miguel
2001-01-01
Research on the exchange bias (EB) phenomenon has witnessed a flurry of activity during recent years, which stems from its use in magnetic sensors and as stabilizers in magnetic reading heads. EB was discovered in 1956 but it attracted only limited attention until these applications, closely related to giant magnetoresistance, were developed during the last decade. In this review, I initially give a short introduction, listing the most salient experimental results and what is required from an EB theory. Next, I indicate some of the obstacles in the road towards a satisfactory understanding of the phenomenon. The main body of the text reviews and critically discusses the activity that has flourished, mainly during the last 5 years, in the theoretical front. Finally, an evaluation of the progress made, and a critical assessment as to where we stand nowadays along the road to a satisfactory theory, is presented
Bias modification training can alter approach bias and chocolate consumption.
Schumacher, Sophie E; Kemps, Eva; Tiggemann, Marika
2016-01-01
Recent evidence has demonstrated that bias modification training has potential to reduce cognitive biases for attractive targets and affect health behaviours. The present study investigated whether cognitive bias modification training could be applied to reduce approach bias for chocolate and affect subsequent chocolate consumption. A sample of 120 women (18-27 years) were randomly assigned to an approach-chocolate condition or avoid-chocolate condition, in which they were trained to approach or avoid pictorial chocolate stimuli, respectively. Training had the predicted effect on approach bias, such that participants trained to approach chocolate demonstrated an increased approach bias to chocolate stimuli whereas participants trained to avoid such stimuli showed a reduced bias. Further, participants trained to avoid chocolate ate significantly less of a chocolate muffin in a subsequent taste test than participants trained to approach chocolate. Theoretically, results provide support for the dual process model's conceptualisation of consumption as being driven by implicit processes such as approach bias. In practice, approach bias modification may be a useful component of interventions designed to curb the consumption of unhealthy foods. Copyright © 2015 Elsevier Ltd. All rights reserved.
Automatic generation of biasing parameters for MORSE shielding problems
International Nuclear Information System (INIS)
Hoogenboom, J.E.
1995-01-01
It would be favourable if the biasing functions could be obtained from the Monte Carlo calculation itself. This is discussed in this paper as well as the way to obtain biasing parameters from it for splitting, Russian roulette and path length stretching. The method is demonstrated for a shielding problem solved with the MORSE-SGC/S Monte Carlo code of the SCALE-system. (K.A.)
Indian Academy of Sciences (India)
inference and finite population sampling. Sudhakar Kunte. Elements of statistical computing are discussed in this series. ... which captain gets an option to decide whether to field first or bat first ... may of course not be fair, in the sense that the team which wins ... describe two methods of drawing a random number between 0.
Schrödinger, Erwin
1952-01-01
Nobel Laureate's brilliant attempt to develop a simple, unified standard method of dealing with all cases of statistical thermodynamics - classical, quantum, Bose-Einstein, Fermi-Dirac, and more.The work also includes discussions of Nernst theorem, Planck's oscillator, fluctuations, the n-particle problem, problem of radiation, much more.
Biro, Peter A
2013-02-01
Sampling animals from the wild for study is something nearly every biologist has done, but despite our best efforts to obtain random samples of animals, 'hidden' trait biases may still exist. For example, consistent behavioral traits can affect trappability/catchability, independent of obvious factors such as size and gender, and these traits are often correlated with other repeatable physiological and/or life history traits. If so, systematic sampling bias may exist for any of these traits. The extent to which this is a problem, of course, depends on the magnitude of bias, which is presently unknown because the underlying trait distributions in populations are usually unknown, or unknowable. Indeed, our present knowledge about sampling bias comes from samples (not complete population censuses), which can possess bias to begin with. I had the unique opportunity to create naturalized populations of fish by seeding each of four small fishless lakes with equal densities of slow-, intermediate-, and fast-growing fish. Using sampling methods that are not size-selective, I observed that fast-growing fish were up to two-times more likely to be sampled than slower-growing fish. This indicates substantial and systematic bias with respect to an important life history trait (growth rate). If correlations between behavioral, physiological and life-history traits are as widespread as the literature suggests, then many animal samples may be systematically biased with respect to these traits (e.g., when collecting animals for laboratory use), and affect our inferences about population structure and abundance. I conclude with a discussion on ways to minimize sampling bias for particular physiological/behavioral/life-history types within animal populations.
Moisture Forecast Bias Correction in GEOS DAS
Dee, D.
1999-01-01
Data assimilation methods rely on numerous assumptions about the errors involved in measuring and forecasting atmospheric fields. One of the more disturbing of these is that short-term model forecasts are assumed to be unbiased. In case of atmospheric moisture, for example, observational evidence shows that the systematic component of errors in forecasts and analyses is often of the same order of magnitude as the random component. we have implemented a sequential algorithm for estimating forecast moisture bias from rawinsonde data in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The algorithm is designed to remove the systematic component of analysis errors and can be easily incorporated in an existing statistical data assimilation system. We will present results of initial experiments that show a significant reduction of bias in the GEOS DAS moisture analyses.
Is there gender bias in nursing research?
Polit, Denise F; Beck, Cheryl Tatano
2008-10-01
Using data from a consecutive sample of 259 studies published in four leading nursing research journals in 2005-2006, we examined whether nurse researchers favor females as study participants. On average, 75.3% of study participants were female, and 38% of studies had all-female samples. The bias favoring female participants was statistically significant and persistent. The bias was observed regardless of funding source, methodological features, and other participant and researcher characteristics, with one exception: studies that had male investigators had more sex-balanced samples. When designing studies, nurse researchers need to pay close attention to who will benefit from their research and to whether they are leaving out a specific group about which there is a gap in knowledge. (c) 2008 Wiley Periodicals, Inc.
Religious Attitudes and Home Bias
C. Reggiani; G. Rossini
2008-01-01
Home bias affects trade in goods, services and financial assets. It is mostly generated by "natural" trade barriers. Among these dividers we may list many behavioral and sociological factors, such as status quo biases and a few kind of ‘embeddedness’. Unfortunately these factors are difficult to measure. An important part of ‘embeddedness’ may be related to religious attitudes. Is there any relation between economic home bias and religious attitudes at the individual tier? Our aim is to provi...
Spatial Bias in Field-Estimated Unsaturated Hydraulic Properties
Energy Technology Data Exchange (ETDEWEB)
HOLT,ROBERT M.; WILSON,JOHN L.; GLASS JR.,ROBERT J.
2000-12-21
Hydraulic property measurements often rely on non-linear inversion models whose errors vary between samples. In non-linear physical measurement systems, bias can be directly quantified and removed using calibration standards. In hydrologic systems, field calibration is often infeasible and bias must be quantified indirectly. We use a Monte Carlo error analysis to indirectly quantify spatial bias in the saturated hydraulic conductivity, K{sub s}, and the exponential relative permeability parameter, {alpha}, estimated using a tension infiltrometer. Two types of observation error are considered, along with one inversion-model error resulting from poor contact between the instrument and the medium. Estimates of spatial statistics, including the mean, variance, and variogram-model parameters, show significant bias across a parameter space representative of poorly- to well-sorted silty sand to very coarse sand. When only observation errors are present, spatial statistics for both parameters are best estimated in materials with high hydraulic conductivity, like very coarse sand. When simple contact errors are included, the nature of the bias changes dramatically. Spatial statistics are poorly estimated, even in highly conductive materials. Conditions that permit accurate estimation of the statistics for one of the parameters prevent accurate estimation for the other; accurate regions for the two parameters do not overlap in parameter space. False cross-correlation between estimated parameters is created because estimates of K{sub s} also depend on estimates of {alpha} and both parameters are estimated from the same data.
Bias in clinical intervention research
DEFF Research Database (Denmark)
Gluud, Lise Lotte
2006-01-01
Research on bias in clinical trials may help identify some of the reasons why investigators sometimes reach the wrong conclusions about intervention effects. Several quality components for the assessment of bias control have been suggested, but although they seem intrinsically valid, empirical...... evidence is needed to evaluate their effects on the extent and direction of bias. This narrative review summarizes the findings of methodological studies on the influence of bias in clinical trials. A number of methodological studies suggest that lack of adequate randomization in published trial reports...
International Nuclear Information System (INIS)
Anon.
1994-01-01
For the years 1992 and 1993, 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. The tables and figures shown in this publication are: Changes in the volume of GNP and energy consumption; Coal consumption; Natural gas consumption; Peat consumption; Domestic oil deliveries; Import prices of oil; Price development of principal oil products; Fuel prices for power production; Total energy consumption by source; Electricity supply; Energy imports by country of origin in 1993; Energy exports by recipient country in 1993; Consumer prices of liquid fuels; Consumer prices of hard coal and natural gas, prices of indigenous fuels; Average electricity price by type of consumer; Price of district heating by type of consumer and Excise taxes and turnover taxes included in consumer prices of some energy sources
Goodman, Joseph W.
2000-07-01
The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson The Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences Robert G. Bartle The Elements of Integration and Lebesgue Measure George E. P. Box & Norman R. Draper Evolutionary Operation: A Statistical Method for Process Improvement George E. P. Box & George C. Tiao Bayesian Inference in Statistical Analysis R. W. Carter Finite Groups of Lie Type: Conjugacy Classes and Complex Characters R. W. Carter Simple Groups of Lie Type William G. Cochran & Gertrude M. Cox Experimental Designs, Second Edition Richard Courant Differential and Integral Calculus, Volume I RIchard Courant Differential and Integral Calculus, Volume II Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume I Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume II D. R. Cox Planning of Experiments Harold S. M. Coxeter Introduction to Geometry, Second Edition Charles W. Curtis & Irving Reiner Representation Theory of Finite Groups and Associative Algebras Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume I Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume II Cuthbert Daniel Fitting Equations to Data: Computer Analysis of Multifactor Data, Second Edition Bruno de Finetti Theory of Probability, Volume I Bruno de Finetti Theory of Probability, Volume 2 W. Edwards Deming Sample Design in Business Research
Pivato, Marcus
2013-01-01
We show that, in a sufficiently large population satisfying certain statistical regularities, it is often possible to accurately estimate the utilitarian social welfare function, even if we only have very noisy data about individual utility functions and interpersonal utility comparisons. In particular, we show that it is often possible to identify an optimal or close-to-optimal utilitarian social choice using voting rules such as the Borda rule, approval voting, relative utilitarianism, or a...
Natrella, Mary Gibbons
1963-01-01
Formulated to assist scientists and engineers engaged in army ordnance research and development programs, this well-known and highly regarded handbook is a ready reference for advanced undergraduate and graduate students as well as for professionals seeking engineering information and quantitative data for designing, developing, constructing, and testing equipment. Topics include characterizing and comparing the measured performance of a material, product, or process; general considerations in planning experiments; statistical techniques for analyzing extreme-value data; use of transformations
Information environment, behavioral biases, and home bias in analysts’ recommendations
DEFF Research Database (Denmark)
Farooq, Omar; Taouss, Mohammed
2012-01-01
Can information environment of a firm explain home bias in analysts’ recommendations? Can the extent of agency problems explain optimism difference between foreign and local analysts? This paper answers these questions by documenting the effect of information environment on home bias in analysts’...
Threat bias, not negativity bias, underpins differences in political ideology.
Lilienfeld, Scott O; Latzman, Robert D
2014-06-01
Although disparities in political ideology are rooted partly in dispositional differences, Hibbing et al.'s analysis paints with an overly broad brush. Research on the personality correlates of liberal-conservative differences points not to global differences in negativity bias, but to differences in threat bias, probably emanating from differences in fearfulness. This distinction bears implications for etiological research and persuasion efforts.
... obtained from the 2008 National Health Interview Survey (NHIS); (2) the estimated number of American adults reporting ... collected by (1) the National Health Interview Survey (NHIS) annually for number of persons who have ever ...
Directory of Open Access Journals (Sweden)
Plant Ramona N
2006-08-01
Full Text Available Abstract Background Whole genome amplification is an increasingly common technique through which minute amounts of DNA can be multiplied to generate quantities suitable for genetic testing and analysis. Questions of amplification-induced error and template bias generated by these methods have previously been addressed through either small scale (SNPs or large scale (CGH array, FISH methodologies. Here we utilized whole genome sequencing to assess amplification-induced bias in both coding and non-coding regions of two bacterial genomes. Halobacterium species NRC-1 DNA and Campylobacter jejuni were amplified by several common, commercially available protocols: multiple displacement amplification, primer extension pre-amplification and degenerate oligonucleotide primed PCR. The amplification-induced bias of each method was assessed by sequencing both genomes in their entirety using the 454 Sequencing System technology and comparing the results with those obtained from unamplified controls. Results All amplification methodologies induced statistically significant bias relative to the unamplified control. For the Halobacterium species NRC-1 genome, assessed at 100 base resolution, the D-statistics from GenomiPhi-amplified material were 119 times greater than those from unamplified material, 164.0 times greater for Repli-G, 165.0 times greater for PEP-PCR and 252.0 times greater than the unamplified controls for DOP-PCR. For Campylobacter jejuni, also analyzed at 100 base resolution, the D-statistics from GenomiPhi-amplified material were 15 times greater than those from unamplified material, 19.8 times greater for Repli-G, 61.8 times greater for PEP-PCR and 220.5 times greater than the unamplified controls for DOP-PCR. Conclusion Of the amplification methodologies examined in this paper, the multiple displacement amplification products generated the least bias, and produced significantly higher yields of amplified DNA.
Biased Monte Carlo optimization: the basic approach
International Nuclear Information System (INIS)
Campioni, Luca; Scardovelli, Ruben; Vestrucci, Paolo
2005-01-01
It is well-known that the Monte Carlo method is very successful in tackling several kinds of system simulations. It often happens that one has to deal with rare events, and the use of a variance reduction technique is almost mandatory, in order to have Monte Carlo efficient applications. The main issue associated with variance reduction techniques is related to the choice of the value of the biasing parameter. Actually, this task is typically left to the experience of the Monte Carlo user, who has to make many attempts before achieving an advantageous biasing. A valuable result is provided: a methodology and a practical rule addressed to establish an a priori guidance for the choice of the optimal value of the biasing parameter. This result, which has been obtained for a single component system, has the notable property of being valid for any multicomponent system. In particular, in this paper, the exponential and the uniform biases of exponentially distributed phenomena are investigated thoroughly
Zhao, Huaqing; Rebbeck, Timothy R; Mitra, Nandita
2009-12-01
Confounding due to population stratification (PS) arises when differences in both allele and disease frequencies exist in a population of mixed racial/ethnic subpopulations. Genomic control, structured association, principal components analysis (PCA), and multidimensional scaling (MDS) approaches have been proposed to address this bias using genetic markers. However, confounding due to PS can also be due to non-genetic factors. Propensity scores are widely used to address confounding in observational studies but have not been adapted to deal with PS in genetic association studies. We propose a genomic propensity score (GPS) approach to correct for bias due to PS that considers both genetic and non-genetic factors. We compare the GPS method with PCA and MDS using simulation studies. Our results show that GPS can adequately adjust and consistently correct for bias due to PS. Under no/mild, moderate, and severe PS, GPS yielded estimated with bias close to 0 (mean=-0.0044, standard error=0.0087). Under moderate or severe PS, the GPS method consistently outperforms the PCA method in terms of bias, coverage probability (CP), and type I error. Under moderate PS, the GPS method consistently outperforms the MDS method in terms of CP. PCA maintains relatively high power compared to both MDS and GPS methods under the simulated situations. GPS and MDS are comparable in terms of statistical properties such as bias, type I error, and power. The GPS method provides a novel and robust tool for obtaining less-biased estimates of genetic associations that can consider both genetic and non-genetic factors. 2009 Wiley-Liss, Inc.
DEFF Research Database (Denmark)
Ranaboldo, Matteo; Giebel, Gregor; Codina, Bernat
2013-01-01
A combination of physical and statistical treatments to post‐process numerical weather predictions (NWP) outputs is needed for successful short‐term wind power forecasts. One of the most promising and effective approaches for statistical treatment is the Model Output Statistics (MOS) technique....... The proposed MOS performed well in both wind farms, and its forecasts compare positively with an actual operative model in use at Risø DTU and other MOS types, showing minimum BIAS and improving NWP power forecast of around 15% in terms of root mean square error. Further improvements could be obtained...
Heuristic Biases in Mathematical Reasoning
Inglis, Matthew; Simpson, Adrian
2005-01-01
In this paper we briefly describe the dual process account of reasoning, and explain the role of heuristic biases in human thought. Concentrating on the so-called matching bias effect, we describe a piece of research that indicates a correlation between success at advanced level mathematics and an ability to override innate and misleading…
Gender bias affects forests worldwide
Marlène Elias; Susan S Hummel; Bimbika S Basnett; Carol J.P. Colfer
2017-01-01
Gender biases persist in forestry research and practice. These biases result in reduced scientific rigor and inequitable, ineffective, and less efficient policies, programs, and interventions. Drawing from a two-volume collection of current and classic analyses on gender in forests, we outline five persistent and inter-related themes: gendered governance, tree tenure,...
Anti-Bias Education: Reflections
Derman-Sparks, Louise
2011-01-01
It is 30 years since NAEYC published "Anti-Bias Curriculum Tools for Empowering Young Children" (Derman-Sparks & ABC Task Force, 1989). Since then, anti-bias education concepts have become part of the early childhood education (ECE) narrative in the United States and many other countries. It has brought a fresh way of thinking about…
International Nuclear Information System (INIS)
Anon.
1989-01-01
World data from the United Nation's latest Energy Statistics Yearbook, first published in our last issue, are completed here. The 1984-86 data were revised and 1987 data added for world commercial energy production and consumption, world natural gas plant liquids production, world LP-gas production, imports, exports, and consumption, world residual fuel oil production, imports, exports, and consumption, world lignite production, imports, exports, and consumption, world peat production and consumption, world electricity production, imports, exports, and consumption (Table 80), and world nuclear electric power production
Gaussian statistics for palaeomagnetic vectors
Love, J.J.; Constable, C.G.
2003-01-01
With the aim of treating the statistics of palaeomagnetic directions and intensities jointly and consistently, we represent the mean and the variance of palaeomagnetic vectors, at a particular site and of a particular polarity, by a probability density function in a Cartesian three-space of orthogonal magnetic-field components consisting of a single (unimoda) non-zero mean, spherically-symmetrical (isotropic) Gaussian function. For palaeomagnetic data of mixed polarities, we consider a bimodal distribution consisting of a pair of such symmetrical Gaussian functions, with equal, but opposite, means and equal variances. For both the Gaussian and bi-Gaussian distributions, and in the spherical three-space of intensity, inclination, and declination, we obtain analytical expressions for the marginal density functions, the cumulative distributions, and the expected values and variances for each spherical coordinate (including the angle with respect to the axis of symmetry of the distributions). The mathematical expressions for the intensity and off-axis angle are closed-form and especially manageable, with the intensity distribution being Rayleigh-Rician. In the limit of small relative vectorial dispersion, the Gaussian (bi-Gaussian) directional distribution approaches a Fisher (Bingham) distribution and the intensity distribution approaches a normal distribution. In the opposite limit of large relative vectorial dispersion, the directional distributions approach a spherically-uniform distribution and the intensity distribution approaches a Maxwell distribution. We quantify biases in estimating the properties of the vector field resulting from the use of simple arithmetic averages, such as estimates of the intensity or the inclination of the mean vector, or the variances of these quantities. With the statistical framework developed here and using the maximum-likelihood method, which gives unbiased estimates in the limit of large data numbers, we demonstrate how to
Gaussian statistics for palaeomagnetic vectors
Love, J. J.; Constable, C. G.
2003-03-01
With the aim of treating the statistics of palaeomagnetic directions and intensities jointly and consistently, we represent the mean and the variance of palaeomagnetic vectors, at a particular site and of a particular polarity, by a probability density function in a Cartesian three-space of orthogonal magnetic-field components consisting of a single (unimodal) non-zero mean, spherically-symmetrical (isotropic) Gaussian function. For palaeomagnetic data of mixed polarities, we consider a bimodal distribution consisting of a pair of such symmetrical Gaussian functions, with equal, but opposite, means and equal variances. For both the Gaussian and bi-Gaussian distributions, and in the spherical three-space of intensity, inclination, and declination, we obtain analytical expressions for the marginal density functions, the cumulative distributions, and the expected values and variances for each spherical coordinate (including the angle with respect to the axis of symmetry of the distributions). The mathematical expressions for the intensity and off-axis angle are closed-form and especially manageable, with the intensity distribution being Rayleigh-Rician. In the limit of small relative vectorial dispersion, the Gaussian (bi-Gaussian) directional distribution approaches a Fisher (Bingham) distribution and the intensity distribution approaches a normal distribution. In the opposite limit of large relative vectorial dispersion, the directional distributions approach a spherically-uniform distribution and the intensity distribution approaches a Maxwell distribution. We quantify biases in estimating the properties of the vector field resulting from the use of simple arithmetic averages, such as estimates of the intensity or the inclination of the mean vector, or the variances of these quantities. With the statistical framework developed here and using the maximum-likelihood method, which gives unbiased estimates in the limit of large data numbers, we demonstrate how to
Taniguchi, Hidetaka; Sato, Hiroshi; Shirakawa, Tomohiro
2018-05-09
Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning. Here, we developed a method to reduce the gap between human beings and machines in this type of inference by utilizing cognitive biases. We implemented a human cognitive model into machine learning algorithms and compared their performance with the currently most popular methods, naïve Bayes, support vector machine, neural networks, logistic regression and random forests. We focused on the task of spam classification, which has been studied for a long time in the field of machine learning and often requires a large amount of data to obtain high accuracy. Our models achieved superior performance with small and biased samples in comparison with other representative machine learning methods.
Single-Receiver GPS Phase Bias Resolution
Bertiger, William I.; Haines, Bruce J.; Weiss, Jan P.; Harvey, Nathaniel E.
2010-01-01
Existing software has been modified to yield the benefits of integer fixed double-differenced GPS-phased ambiguities when processing data from a single GPS receiver with no access to any other GPS receiver data. When the double-differenced combination of phase biases can be fixed reliably, a significant improvement in solution accuracy is obtained. This innovation uses a large global set of GPS receivers (40 to 80 receivers) to solve for the GPS satellite orbits and clocks (along with any other parameters). In this process, integer ambiguities are fixed and information on the ambiguity constraints is saved. For each GPS transmitter/receiver pair, the process saves the arc start and stop times, the wide-lane average value for the arc, the standard deviation of the wide lane, and the dual-frequency phase bias after bias fixing for the arc. The second step of the process uses the orbit and clock information, the bias information from the global solution, and only data from the single receiver to resolve double-differenced phase combinations. It is called "resolved" instead of "fixed" because constraints are introduced into the problem with a finite data weight to better account for possible errors. A receiver in orbit has much shorter continuous passes of data than a receiver fixed to the Earth. The method has parameters to account for this. In particular, differences in drifting wide-lane values must be handled differently. The first step of the process is automated, using two JPL software sets, Longarc and Gipsy-Oasis. The resulting orbit/clock and bias information files are posted on anonymous ftp for use by any licensed Gipsy-Oasis user. The second step is implemented in the Gipsy-Oasis executable, gd2p.pl, which automates the entire process, including fetching the information from anonymous ftp
Energy Technology Data Exchange (ETDEWEB)
Callister, Stephen J.; Barry, Richard C.; Adkins, Joshua N.; Johnson, Ethan T.; Qian, Weijun; Webb-Robertson, Bobbie-Jo M.; Smith, Richard D.; Lipton, Mary S.
2006-02-01
Central tendency, linear regression, locally weighted regression, and quantile techniques were investigated for normalization of peptide abundance measurements obtained from high-throughput liquid chromatography-Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR MS). Arbitrary abundances of peptides were obtained from three sample sets, including a standard protein sample, two Deinococcus radiodurans samples taken from different growth phases, and two mouse striatum samples from control and methamphetamine-stressed mice (strain C57BL/6). The selected normalization techniques were evaluated in both the absence and presence of biological variability by estimating extraneous variability prior to and following normalization. Prior to normalization, replicate runs from each sample set were observed to be statistically different, while following normalization replicate runs were no longer statistically different. Although all techniques reduced systematic bias, assigned ranks among the techniques revealed significant trends. For most LC-FTICR MS analyses, linear regression normalization ranked either first or second among the four techniques, suggesting that this technique was more generally suitable for reducing systematic biases.
Publication bias in dermatology systematic reviews and meta-analyses.
Atakpo, Paul; Vassar, Matt
2016-05-01
Systematic reviews and meta-analyses in dermatology provide high-level evidence for clinicians and policy makers that influence clinical decision making and treatment guidelines. One methodological problem with systematic reviews is the under representation of unpublished studies. This problem is due in part to publication bias. Omission of statistically non-significant data from meta-analyses may result in overestimation of treatment effect sizes which may lead to clinical consequences. Our goal was to assess whether systematic reviewers in dermatology evaluate and report publication bias. Further, we wanted to conduct our own evaluation of publication bias on meta-analyses that failed to do so. Our study considered systematic reviews and meta-analyses from ten dermatology journals from 2006 to 2016. A PubMed search was conducted, and all full-text articles that met our inclusion criteria were retrieved and coded by the primary author. 293 articles were included in our analysis. Additionally, we formally evaluated publication bias in meta-analyses that failed to do so using trim and fill and cumulative meta-analysis by precision methods. Publication bias was mentioned in 107 articles (36.5%) and was formally evaluated in 64 articles (21.8%). Visual inspection of a funnel plot was the most common method of evaluating publication bias. Publication bias was present in 45 articles (15.3%), not present in 57 articles (19.5%) and not determined in 191 articles (65.2%). Using the trim and fill method, 7 meta-analyses (33.33%) showed evidence of publication bias. Although the trim and fill method only found evidence of publication bias in 7 meta-analyses, the cumulative meta-analysis by precision method found evidence of publication bias in 15 meta-analyses (71.4%). Many of the reviews in our study did not mention or evaluate publication bias. Further, of the 42 articles that stated following PRISMA reporting guidelines, 19 (45.2%) evaluated for publication bias. In
DEFF Research Database (Denmark)
Bose, Prosenjit; Fagerberg, Rolf; Howat, John
2016-01-01
We consider the problem of performing predecessor searches in a bounded universe while achieving query times that depend on the distribution of queries. We obtain several data structures with various properties: in particular, we give data structures that achieve expected query times logarithmic...
DEFF Research Database (Denmark)
Bose, Prosenjit; Fagerberg, Rolf; Howat, John
2014-01-01
We consider the problem of performing predecessor searches in a bounded universe while achieving query times that depend on the distribution of queries. We obtain several data structures with various properties: in particular, we give data structures that achieve expected query times logarithmic...
Blind signal processing algorithms under DC biased Gaussian noise
Kim, Namyong; Byun, Hyung-Gi; Lim, Jeong-Ok
2013-05-01
Distortions caused by the DC-biased laser input can be modeled as DC biased Gaussian noise and removing DC bias is important in the demodulation process of the electrical signal in most optical communications. In this paper, a new performance criterion and a related algorithm for unsupervised equalization are proposed for communication systems in the environment of channel distortions and DC biased Gaussian noise. The proposed criterion utilizes the Euclidean distance between the Dirac-delta function located at zero on the error axis and a probability density function of biased constant modulus errors, where constant modulus error is defined by the difference between the system out and a constant modulus calculated from the transmitted symbol points. From the results obtained from the simulation under channel models with fading and DC bias noise abruptly added to background Gaussian noise, the proposed algorithm converges rapidly even after the interruption of DC bias proving that the proposed criterion can be effectively applied to optical communication systems corrupted by channel distortions and DC bias noise.
Angular biasing in implicit Monte-Carlo
International Nuclear Information System (INIS)
Zimmerman, G.B.
1994-01-01
Calculations of indirect drive Inertial Confinement Fusion target experiments require an integrated approach in which laser irradiation and radiation transport in the hohlraum are solved simultaneously with the symmetry, implosion and burn of the fuel capsule. The Implicit Monte Carlo method has proved to be a valuable tool for the two dimensional radiation transport within the hohlraum, but the impact of statistical noise on the symmetric implosion of the small fuel capsule is difficult to overcome. We present an angular biasing technique in which an increased number of low weight photons are directed at the imploding capsule. For typical parameters this reduces the required computer time for an integrated calculation by a factor of 10. An additional factor of 5 can also be achieved by directing even smaller weight photons at the polar regions of the capsule where small mass zones are most sensitive to statistical noise
Cognitive Bias in Systems Verification
Larson, Steve
2012-01-01
Working definition of cognitive bias: Patterns by which information is sought and interpreted that can lead to systematic errors in decisions. Cognitive bias is used in diverse fields: Economics, Politics, Intelligence, Marketing, to name a few. Attempts to ground cognitive science in physical characteristics of the cognitive apparatus exceed our knowledge. Studies based on correlations; strict cause and effect is difficult to pinpoint. Effects cited in the paper and discussed here have been replicated many times over, and appear sound. Many biases have been described, but it is still unclear whether they are all distinct. There may only be a handful of fundamental biases, which manifest in various ways. Bias can effect system verification in many ways . Overconfidence -> Questionable decisions to deploy. Availability -> Inability to conceive critical tests. Representativeness -> Overinterpretation of results. Positive Test Strategies -> Confirmation bias. Debiasing at individual level very difficult. The potential effect of bias on the verification process can be managed, but not eliminated. Worth considering at key points in the process.
Administrative bias in South Africa
Directory of Open Access Journals (Sweden)
E S Nwauche
2005-01-01
Full Text Available This article reviews the interpretation of section 6(2(aii of the Promotion of Administrative Justice Act which makes an administrator “biased or reasonably suspected of bias” a ground of judicial review. In this regard, the paper reviews the determination of administrative bias in South Africa especially highlighting the concept of institutional bias. The paper notes that inspite of the formulation of the bias ground of review the test for administrative bias is the reasonable apprehension test laid down in the case of President of South Africa v South African Rugby Football Union(2 which on close examination is not the same thing. Accordingly the paper urges an alternative interpretation that is based on the reasonable suspicion test enunciated in BTR Industries South Africa (Pty Ltd v Metal and Allied Workers Union and R v Roberts. Within this context, the paper constructs a model for interpreting the bias ground of review that combines the reasonable suspicion test as interpreted in BTR Industries and R v Roberts, the possibility of the waiver of administrative bias, the curative mechanism of administrative appeal as well as some level of judicial review exemplified by the jurisprudence of article 6(1 of the European Convention of Human Rights, especially in the light of the contemplation of the South African Magistrate Court as a jurisdictional route of judicial review.
Empirical Comparison of Publication Bias Tests in Meta-Analysis.
Lin, Lifeng; Chu, Haitao; Murad, Mohammad Hassan; Hong, Chuan; Qu, Zhiyong; Cole, Stephen R; Chen, Yong
2018-04-16
Decision makers rely on meta-analytic estimates to trade off benefits and harms. Publication bias impairs the validity and generalizability of such estimates. The performance of various statistical tests for publication bias has been largely compared using simulation studies and has not been systematically evaluated in empirical data. This study compares seven commonly used publication bias tests (i.e., Begg's rank test, trim-and-fill, Egger's, Tang's, Macaskill's, Deeks', and Peters' regression tests) based on 28,655 meta-analyses available in the Cochrane Library. Egger's regression test detected publication bias more frequently than other tests (15.7% in meta-analyses of binary outcomes and 13.5% in meta-analyses of non-binary outcomes). The proportion of statistically significant publication bias tests was greater for larger meta-analyses, especially for Begg's rank test and the trim-and-fill method. The agreement among Tang's, Macaskill's, Deeks', and Peters' regression tests for binary outcomes was moderately strong (most κ's were around 0.6). Tang's and Deeks' tests had fairly similar performance (κ > 0.9). The agreement among Begg's rank test, the trim-and-fill method, and Egger's regression test was weak or moderate (κ < 0.5). Given the relatively low agreement between many publication bias tests, meta-analysts should not rely on a single test and may apply multiple tests with various assumptions. Non-statistical approaches to evaluating publication bias (e.g., searching clinical trials registries, records of drug approving agencies, and scientific conference proceedings) remain essential.
Critical Thinking and Cognitive Bias
Directory of Open Access Journals (Sweden)
Jeffrey Maynes
2015-05-01
Full Text Available Teaching critical thinking skill is a central pedagogical aim in many courses. These skills, it is hoped, will be both portable (applicable in a wide range of contexts and durable (not forgotten quickly. Yet, both of these virtues are challenged by pervasive and potent cognitive biases, such as motivated reasoning, false consensus bias and hindsight bias. In this paper, I argue that a focus on the development of metacognitive skill shows promise as a means to inculcate debiasing habits in students. Such habits will help students become more critical reasoners. I close with suggestions for implementing this strategy.
A comparator-hypothesis account of biased contingency detection.
Vadillo, Miguel A; Barberia, Itxaso
2018-02-12
Our ability to detect statistical dependencies between different events in the environment is strongly biased by the number of coincidences between them. Even when there is no true covariation between a cue and an outcome, if the marginal probability of either of them is high, people tend to perceive some degree of statistical contingency between both events. The present paper explores the ability of the Comparator Hypothesis to explain the general pattern of results observed in this literature. Our simulations show that this model can account for the biasing effects of the marginal probabilities of cues and outcomes. Furthermore, the overall fit of the Comparator Hypothesis to a sample of experimental conditions from previous studies is comparable to that of the popular Rescorla-Wagner model. These results should encourage researchers to further explore and put to the test the predictions of the Comparator Hypothesis in the domain of biased contingency detection. Copyright © 2018 Elsevier B.V. All rights reserved.
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.
Lidar measurements of plume statistics
DEFF Research Database (Denmark)
Ejsing Jørgensen, Hans; Mikkelsen, T.
1993-01-01
of measured crosswind concentration profiles, the following statistics were obtained: 1) Mean profile, 2) Root mean square profile, 3) Fluctuation intensities,and 4)Intermittency factors. Furthermore, some experimentally determined probability density functions (pdf's) of the fluctuations are presented. All...... the measured statistics are referred to a fixed and a 'moving' frame of reference, the latter being defined as a frame of reference from which the (low frequency) plume meander is removed. Finally, the measured statistics are compared with statistics on concentration fluctuations obtained with a simple puff...
Statistical implications in Monte Carlo depletions - 051
International Nuclear Information System (INIS)
Zhiwen, Xu; Rhodes, J.; Smith, K.
2010-01-01
As a result of steady advances of computer power, continuous-energy Monte Carlo depletion analysis is attracting considerable attention for reactor burnup calculations. The typical Monte Carlo analysis is set up as a combination of a Monte Carlo neutron transport solver and a fuel burnup solver. Note that the burnup solver is a deterministic module. The statistical errors in Monte Carlo solutions are introduced into nuclide number densities and propagated along fuel burnup. This paper is towards the understanding of the statistical implications in Monte Carlo depletions, including both statistical bias and statistical variations in depleted fuel number densities. The deterministic Studsvik lattice physics code, CASMO-5, is modified to model the Monte Carlo depletion. The statistical bias in depleted number densities is found to be negligible compared to its statistical variations, which, in turn, demonstrates the correctness of the Monte Carlo depletion method. Meanwhile, the statistical variation in number densities generally increases with burnup. Several possible ways of reducing the statistical errors are discussed: 1) to increase the number of individual Monte Carlo histories; 2) to increase the number of time steps; 3) to run additional independent Monte Carlo depletion cases. Finally, a new Monte Carlo depletion methodology, called the batch depletion method, is proposed, which consists of performing a set of independent Monte Carlo depletions and is thus capable of estimating the overall statistical errors including both the local statistical error and the propagated statistical error. (authors)
Bias in regression coefficient estimates upon different treatments of ...
African Journals Online (AJOL)
MS and PW consistently overestimated the population parameter. EM and RI, on the other hand, tended to consistently underestimate the population parameter under non-monotonic pattern. Keywords: Missing data, bias, regression, percent missing, non-normality, missing pattern > East African Journal of Statistics Vol.
Obesity, the endocannabinoid system, and bias arising from pharmaceutical sponsorship.
Directory of Open Access Journals (Sweden)
John M McPartland
Full Text Available Previous research has shown that academic physicians conflicted by funding from the pharmaceutical industry have corrupted evidence based medicine and helped enlarge the market for drugs. Physicians made pharmaceutical-friendly statements, engaged in disease mongering, and signed biased review articles ghost-authored by corporate employees. This paper tested the hypothesis that bias affects review articles regarding rimonabant, an anti-obesity drug that blocks the central cannabinoid receptor.A MEDLINE search was performed for rimonabant review articles, limited to articles authored by USA physicians who served as consultants for the company that manufactures rimonabant. Extracted articles were examined for industry-friendly bias, identified by three methods: analysis with a validated instrument for monitoring bias in continuing medical education (CME; analysis for bias defined as statements that ran contrary to external evidence; and a tally of misrepresentations about the endocannabinoid system. Eight review articles were identified, but only three disclosed authors' financial conflicts of interest, despite easily accessible information to the contrary. The Takhar CME bias instrument demonstrated statistically significant bias in all the review articles. Biased statements that were nearly identical reappeared in the articles, including disease mongering, exaggerating rimonabant's efficacy and safety, lack of criticisms regarding rimonabant clinical trials, and speculations about surrogate markers stated as facts. Distinctive and identical misrepresentations regarding the endocannabinoid system also reappeared in articles by different authors.The findings are characteristic of bias that arises from financial conflicts of interest, and suggestive of ghostwriting by a common author. Resolutions for this scenario are proposed.
Tellinghuisen, Joel
2008-01-01
The method of least squares is probably the most powerful data analysis tool available to scientists. Toward a fuller appreciation of that power, this work begins with an elementary review of statistics fundamentals, and then progressively increases in sophistication as the coverage is extended to the theory and practice of linear and nonlinear least squares. The results are illustrated in application to data analysis problems important in the life sciences. The review of fundamentals includes the role of sampling and its connection to probability distributions, the Central Limit Theorem, and the importance of finite variance. Linear least squares are presented using matrix notation, and the significance of the key probability distributions-Gaussian, chi-square, and t-is illustrated with Monte Carlo calculations. The meaning of correlation is discussed, including its role in the propagation of error. When the data themselves are correlated, special methods are needed for the fitting, as they are also when fitting with constraints. Nonlinear fitting gives rise to nonnormal parameter distributions, but the 10% Rule of Thumb suggests that such problems will be insignificant when the parameter is sufficiently well determined. Illustrations include calibration with linear and nonlinear response functions, the dangers inherent in fitting inverted data (e.g., Lineweaver-Burk equation), an analysis of the reliability of the van't Hoff analysis, the problem of correlated data in the Guggenheim method, and the optimization of isothermal titration calorimetry procedures using the variance-covariance matrix for experiment design. The work concludes with illustrations on assessing and presenting results.
Automaticity of cognitive biases in addictive behaviours: further evidence with gamblers.
McCusker, C G; Gettings, B
1997-11-01
The hypotheses that automatic, non-volitional, attentional and memory biases for addiction-related constructs exist is tested with compulsive gamblers. An independent groups design was employed. Processing of gambling, compared to neutral and drug-related information was examined in 15 gamblers recruited from new members of Gamblers Anonymous. Comparisons were made with the performance of their spouses (N = 15) to help distinguish addiction mechanisms from more non-specific emotional experiences with gambling, and an independent control group (N = 15), recruited from the staff and students of a university department. A modified Stroop procedure was first employed. Automative cognitive interference was assessed relatively, by comparing colour-naming times on the gambling, drug and neutral Stroops. A subsequent word-stem completion task of implicit memory was then used to assess selective and automatic priming of the gambling constructs in memory. Only the gamblers showed selective and automatic interference for gambling-related constructs on the Stroop task. Spouses behaved like the control group on this task. An implicit memory bias for gambling-related words was statistically detected only in the gamblers compared to the control group, although the trend was similar in the comparison with spouses. Further evidence for the specificity of these effects was obtained in subgroup comparisons involving fruit-machine with racing gamblers. Results are generally consistent with an automaticity in the cognitive biases gamblers show for gambling-related information. Implications for cognitive understanding and treatments are highlighted.
Preferences, country bias, and international trade
S. Roy (Santanu); J.M.A. Viaene (Jean-Marie)
1998-01-01
textabstractAnalyzes international trade where consumer preferences exhibit country bias. Why country biases arise; How trade can occur in the presence of country bias; Implication for the pattern of trade and specialization.
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
Sources of method bias in social science research and recommendations on how to control it.
Podsakoff, Philip M; MacKenzie, Scott B; Podsakoff, Nathan P
2012-01-01
Despite the concern that has been expressed about potential method biases, and the pervasiveness of research settings with the potential to produce them, there is disagreement about whether they really are a problem for researchers in the behavioral sciences. Therefore, the purpose of this review is to explore the current state of knowledge about method biases. First, we explore the meaning of the terms "method" and "method bias" and then we examine whether method biases influence all measures equally. Next, we review the evidence of the effects that method biases have on individual measures and on the covariation between different constructs. Following this, we evaluate the procedural and statistical remedies that have been used to control method biases and provide recommendations for minimizing method bias.
The disagreeable behaviour of the kappa statistic.
Flight, Laura; Julious, Steven A
2015-01-01
It is often of interest to measure the agreement between a number of raters when an outcome is nominal or ordinal. The kappa statistic is used as a measure of agreement. The statistic is highly sensitive to the distribution of the marginal totals and can produce unreliable results. Other statistics such as the proportion of concordance, maximum attainable kappa and prevalence and bias adjusted kappa should be considered to indicate how well the kappa statistic represents agreement in the data. Each kappa should be considered and interpreted based on the context of the data being analysed. Copyright © 2014 John Wiley & Sons, Ltd.
Negativity Bias in Dangerous Drivers.
Directory of Open Access Journals (Sweden)
Jing Chai
Full Text Available The behavioral and cognitive characteristics of dangerous drivers differ significantly from those of safe drivers. However, differences in emotional information processing have seldom been investigated. Previous studies have revealed that drivers with higher anger/anxiety trait scores are more likely to be involved in crashes and that individuals with higher anger traits exhibit stronger negativity biases when processing emotions compared with control groups. However, researchers have not explored the relationship between emotional information processing and driving behavior. In this study, we examined the emotional information processing differences between dangerous drivers and safe drivers. Thirty-eight non-professional drivers were divided into two groups according to the penalty points that they had accrued for traffic violations: 15 drivers with 6 or more points were included in the dangerous driver group, and 23 drivers with 3 or fewer points were included in the safe driver group. The emotional Stroop task was used to measure negativity biases, and both behavioral and electroencephalograph data were recorded. The behavioral results revealed stronger negativity biases in the dangerous drivers than in the safe drivers. The bias score was correlated with self-reported dangerous driving behavior. Drivers with strong negativity biases reported having been involved in mores crashes compared with the less-biased drivers. The event-related potentials (ERPs revealed that the dangerous drivers exhibited reduced P3 components when responding to negative stimuli, suggesting decreased inhibitory control of information that is task-irrelevant but emotionally salient. The influence of negativity bias provides one possible explanation of the effects of individual differences on dangerous driving behavior and traffic crashes.
Directory of Open Access Journals (Sweden)
Borbala Mifsud
Full Text Available Hi-C is one of the main methods for investigating spatial co-localisation of DNA in the nucleus. However, the raw sequencing data obtained from Hi-C experiments suffer from large biases and spurious contacts, making it difficult to identify true interactions. Existing methods use complex models to account for biases and do not provide a significance threshold for detecting interactions. Here we introduce a simple binomial probabilistic model that resolves complex biases and distinguishes between true and false interactions. The model corrects biases of known and unknown origin and yields a p-value for each interaction, providing a reliable threshold based on significance. We demonstrate this experimentally by testing the method against a random ligation dataset. Our method outperforms previous methods and provides a statistical framework for further data analysis, such as comparisons of Hi-C interactions between different conditions. GOTHiC is available as a BioConductor package (http://www.bioconductor.org/packages/release/bioc/html/GOTHiC.html.
Mifsud, Borbala; Martincorena, Inigo; Darbo, Elodie; Sugar, Robert; Schoenfelder, Stefan; Fraser, Peter; Luscombe, Nicholas M
2017-01-01
Hi-C is one of the main methods for investigating spatial co-localisation of DNA in the nucleus. However, the raw sequencing data obtained from Hi-C experiments suffer from large biases and spurious contacts, making it difficult to identify true interactions. Existing methods use complex models to account for biases and do not provide a significance threshold for detecting interactions. Here we introduce a simple binomial probabilistic model that resolves complex biases and distinguishes between true and false interactions. The model corrects biases of known and unknown origin and yields a p-value for each interaction, providing a reliable threshold based on significance. We demonstrate this experimentally by testing the method against a random ligation dataset. Our method outperforms previous methods and provides a statistical framework for further data analysis, such as comparisons of Hi-C interactions between different conditions. GOTHiC is available as a BioConductor package (http://www.bioconductor.org/packages/release/bioc/html/GOTHiC.html).
Publication Bias in Meta-Analyses of the Efficacy of Psychotherapeutic Interventions for Depression
Niemeyer, Helen; Musch, Jochen; Pietrowsky, Reinhard
2013-01-01
Objective: The aim of this study was to assess whether systematic reviews investigating psychotherapeutic interventions for depression are affected by publication bias. Only homogeneous data sets were included, as heterogeneous data sets can distort statistical tests of publication bias. Method: We applied Begg and Mazumdar's adjusted rank…
TCABR Tokamak scrape-off layer turbulence with DC biasing
International Nuclear Information System (INIS)
Heller, M.V.A.P.; Ferreira, A.A.; Caldas, I.L.; Nascimento, I.C.
2004-01-01
Turbulence and particle transport in plasma scrape-off layer have been controlled by external electric fields. This control can be achieved by a biasing electrode located inside the plasma. We investigate plasma turbulence changes in the scrape-off layer of TCABR tokamak introduced by DC biasing an electrode inside the plasma. Our investigation is based on the alterations observed on the wavelet power spectra and on the intermittent burst sequences of plasma potential and density fluctuations measured by a set of Langmuir probes. Biasing the electrode changes the turbulence statistics and the bursts intermittence. With the imposed external electric field, fluctuation amplitudes, phase velocities, and anomalous particle transport are modified. Transport reduction for higher frequencies induced by the biasing could be due to the strong de-phasing between density and potential fluctuations. The mode coupling increases with the perturbation for the high frequency broadband fluctuations. The total (laminar and bursting) radial particle transport is reduced by about 25% by DC biasing. Bursts contribution to total transport is 15% and for the studied conditions this contribution does not change much with the bias perturbation
CLIA Statistical Tables and Graphs
U.S. Department of Health & Human Services — The information in the Downloads section below for the Overview of CLIA Statistics since 1993 and the CLIA Top Ten Deficiencies in the Nation was obtained from the...
Statistical interpretation of geochemical data
International Nuclear Information System (INIS)
Carambula, M.
1990-01-01
Statistical results have been obtained from a geochemical research from the following four aerial photographies Zapican, Carape, Las Canias, Alferez. They have been studied 3020 samples in total, to 22 chemical elements using plasma emission spectrometry methods.
Comparison of stability statistics for yield in barley (Hordeum vulgare ...
African Journals Online (AJOL)
STORAGESEVER
2010-03-15
Mar 15, 2010 ... statistics and yield indicated that only TOP method would be useful for simultaneously selecting for high yield and ... metric stability methods; i) they reduce the bias caused by outliers, ii) ...... Biometrics, 43: 45-53. Sabaghnia N ...
ITSA: Internet Traffic Statistics Archive
Hoogesteger, Martijn; de Oliveira Schmidt, R.; Pras, Aiko
Motivated by the fact that comprehensive and long term Internet traffic measurements can be hard to obtain, we have proposed and developed the Internet Traffic Statistics Archive (ITSA). Since 2013, ITSA concentrates reports on high-level statistics of Internet traffic worldwide. Examples of
Cluster Statistics of BTW Automata
International Nuclear Information System (INIS)
Ajanta Bhowal Acharyya
2011-01-01
The cluster statistics of BTW automata in the SOC states are obtained by extensive computer simulation. Various moments of the clusters are calculated and few results are compared with earlier available numerical estimates and exact results. Reasonably good agreement is observed. An extended statistical analysis has been made. (author)
Numerical value biases sound localization.
Golob, Edward J; Lewald, Jörg; Getzmann, Stephan; Mock, Jeffrey R
2017-12-08
Speech recognition starts with representations of basic acoustic perceptual features and ends by categorizing the sound based on long-term memory for word meaning. However, little is known about whether the reverse pattern of lexical influences on basic perception can occur. We tested for a lexical influence on auditory spatial perception by having subjects make spatial judgments of number stimuli. Four experiments used pointing or left/right 2-alternative forced choice tasks to examine perceptual judgments of sound location as a function of digit magnitude (1-9). The main finding was that for stimuli presented near the median plane there was a linear left-to-right bias for localizing smaller-to-larger numbers. At lateral locations there was a central-eccentric location bias in the pointing task, and either a bias restricted to the smaller numbers (left side) or no significant number bias (right side). Prior number location also biased subsequent number judgments towards the opposite side. Findings support a lexical influence on auditory spatial perception, with a linear mapping near midline and more complex relations at lateral locations. Results may reflect coding of dedicated spatial channels, with two representing lateral positions in each hemispace, and the midline area represented by either their overlap or a separate third channel.
Anatomy of the Higgs fits: A first guide to statistical treatments of the theoretical uncertainties
Directory of Open Access Journals (Sweden)
Sylvain Fichet
2016-04-01
Full Text Available The studies of the Higgs boson couplings based on the recent and upcoming LHC data open up a new window on physics beyond the Standard Model. In this paper, we propose a statistical guide to the consistent treatment of the theoretical uncertainties entering the Higgs rate fits. Both the Bayesian and frequentist approaches are systematically analysed in a unified formalism. We present analytical expressions for the marginal likelihoods, useful to implement simultaneously the experimental and theoretical uncertainties. We review the various origins of the theoretical errors (QCD, EFT, PDF, production mode contamination…. All these individual uncertainties are thoroughly combined with the help of moment-based considerations. The theoretical correlations among Higgs detection channels appear to affect the location and size of the best-fit regions in the space of Higgs couplings. We discuss the recurrent question of the shape of the prior distributions for the individual theoretical errors and find that a nearly Gaussian prior arises from the error combinations. We also develop the bias approach, which is an alternative to marginalisation providing more conservative results. The statistical framework to apply the bias principle is introduced and two realisations of the bias are proposed. Finally, depending on the statistical treatment, the Standard Model prediction for the Higgs signal strengths is found to lie within either the 68% or 95% confidence level region obtained from the latest analyses of the 7 and 8 TeV LHC datasets.
Anatomy of the Higgs fits: A first guide to statistical treatments of the theoretical uncertainties
Fichet, Sylvain; Moreau, Grégory
2016-04-01
The studies of the Higgs boson couplings based on the recent and upcoming LHC data open up a new window on physics beyond the Standard Model. In this paper, we propose a statistical guide to the consistent treatment of the theoretical uncertainties entering the Higgs rate fits. Both the Bayesian and frequentist approaches are systematically analysed in a unified formalism. We present analytical expressions for the marginal likelihoods, useful to implement simultaneously the experimental and theoretical uncertainties. We review the various origins of the theoretical errors (QCD, EFT, PDF, production mode contamination…). All these individual uncertainties are thoroughly combined with the help of moment-based considerations. The theoretical correlations among Higgs detection channels appear to affect the location and size of the best-fit regions in the space of Higgs couplings. We discuss the recurrent question of the shape of the prior distributions for the individual theoretical errors and find that a nearly Gaussian prior arises from the error combinations. We also develop the bias approach, which is an alternative to marginalisation providing more conservative results. The statistical framework to apply the bias principle is introduced and two realisations of the bias are proposed. Finally, depending on the statistical treatment, the Standard Model prediction for the Higgs signal strengths is found to lie within either the 68% or 95% confidence level region obtained from the latest analyses of the 7 and 8 TeV LHC datasets.
Directory of Open Access Journals (Sweden)
Jennifer L. Johns
2018-02-01
Full Text Available Clinical pathology testing of rodents is often challenging due to insufficient sample volume. One solution in clinical veterinary and exploratory research environments is dilution of samples prior to analysis. However, published information on the impact of preanalytical sample dilution on rodent biochemical data is incomplete. The objective of this study was to evaluate the effects of preanalytical sample dilution on biochemical analysis of mouse and rat serum samples utilizing the Siemens Dimension Xpand Plus. Rats were obtained from end of study research projects. Mice were obtained from sentinel testing programs. For both, whole blood was collected via terminal cardiocentesis into empty tubes and serum was harvested. Biochemical parameters were measured on fresh and thawed frozen samples run straight and at dilution factors 2–10. Dilutions were performed manually, utilizing either ultrapure water or enzyme diluent per manufacturer recommendations. All diluted samples were generated directly from the undiluted sample. Preanalytical dilution caused clinically unacceptable bias in most analytes at dilution factors four and above. Dilution-induced bias in total calcium, creatinine, total bilirubin, and uric acid was considered unacceptable with any degree of dilution, based on the more conservative of two definitions of acceptability. Dilution often caused electrolyte values to fall below assay range precluding evaluation of bias. Dilution-induced bias occurred in most biochemical parameters to varying degrees and may render dilution unacceptable in the exploratory research and clinical veterinary environments. Additionally, differences between results obtained at different dilution factors may confound statistical comparisons in research settings. Comparison of data obtained at a single dilution factor is highly recommended.
Lamadrid-Figueroa, Héctor; Téllez-Rojo, Martha M; Angeles, Gustavo; Hernández-Ávila, Mauricio; Hu, Howard
2011-01-01
In-vivo measurement of bone lead by means of K-X-ray fluorescence (KXRF) is the preferred biological marker of chronic exposure to lead. Unfortunately, considerable measurement error associated with KXRF estimations can introduce bias in estimates of the effect of bone lead when this variable is included as the exposure in a regression model. Estimates of uncertainty reported by the KXRF instrument reflect the variance of the measurement error and, although they can be used to correct the measurement error bias, they are seldom used in epidemiological statistical analyzes. Errors-in-variables regression (EIV) allows for correction of bias caused by measurement error in predictor variables, based on the knowledge of the reliability of such variables. The authors propose a way to obtain reliability coefficients for bone lead measurements from uncertainty data reported by the KXRF instrument and compare, by the use of Monte Carlo simulations, results obtained using EIV regression models vs. those obtained by the standard procedures. Results of the simulations show that Ordinary Least Square (OLS) regression models provide severely biased estimates of effect, and that EIV provides nearly unbiased estimates. Although EIV effect estimates are more imprecise, their mean squared error is much smaller than that of OLS estimates. In conclusion, EIV is a better alternative than OLS to estimate the effect of bone lead when measured by KXRF. Copyright Â© 2010 Elsevier Inc. All rights reserved.
Bias correction for rainrate retrievals from satellite passive microwave sensors
Short, David A.
1990-01-01
Rainrates retrieved from past and present satellite-borne microwave sensors are affected by a fundamental remote sensing problem. Sensor fields-of-view are typically large enough to encompass substantial rainrate variability, whereas the retrieval algorithms, based on radiative transfer calculations, show a non-linear relationship between rainrate and microwave brightness temperature. Retrieved rainrates are systematically too low. A statistical model of the bias problem shows that bias correction factors depend on the probability distribution of instantaneous rainrate and on the average thickness of the rain layer.
A MORET tool to assist code bias estimation
International Nuclear Information System (INIS)
Fernex, F.; Richet, Y.; Letang, E.
2003-01-01
This new Graphical User Interface (GUI) developed in JAVA is one of the post-processing tools for MORET4 code. It aims to help users to estimate the importance of the k eff bias due to the code in order to better define the upper safety limit. Moreover, it allows visualizing the distance between an actual configuration case and evaluated critical experiments. This tool depends on a validated experiments database, on sets of physical parameters and on various statistical tools allowing interpolating the calculation bias of the database or displaying the projections of experiments on a reduced base of parameters. The development of this tool is still in progress. (author)
Comparison of Statistical Post-Processing Methods for Probabilistic Wind Speed Forecasting
Han, Keunhee; Choi, JunTae; Kim, Chansoo
2018-02-01
In this study, the statistical post-processing methods that include bias-corrected and probabilistic forecasts of wind speed measured in PyeongChang, which is scheduled to host the 2018 Winter Olympics, are compared and analyzed to provide more accurate weather information. The six post-processing methods used in this study are as follows: mean bias-corrected forecast, mean and variance bias-corrected forecast, decaying averaging forecast, mean absolute bias-corrected forecast, and the alternative implementations of ensemble model output statistics (EMOS) and Bayesian model averaging (BMA) models, which are EMOS and BMA exchangeable models by assuming exchangeable ensemble members and simplified version of EMOS and BMA models. Observations for wind speed were obtained from the 26 stations in PyeongChang and 51 ensemble member forecasts derived from the European Centre for Medium-Range Weather Forecasts (ECMWF Directorate, 2012) that were obtained between 1 May 2013 and 18 March 2016. Prior to applying the post-processing methods, reliability analysis was conducted by using rank histograms to identify the statistical consistency of ensemble forecast and corresponding observations. Based on the results of our study, we found that the prediction skills of probabilistic forecasts of EMOS and BMA models were superior to the biascorrected forecasts in terms of deterministic prediction, whereas in probabilistic prediction, BMA models showed better prediction skill than EMOS. Even though the simplified version of BMA model exhibited best prediction skill among the mentioned six methods, the results showed that the differences of prediction skills between the versions of EMOS and BMA were negligible.
Yamada, Yoshitake; Yamada, Minoru; Sugisawa, Koichi; Akita, Hirotaka; Shiomi, Eisuke; Abe, Takayuki; Okuda, Shigeo; Jinzaki, Masahiro
2015-01-01
Abstract The purpose of this study was to compare renal cyst pseudoenhancement between virtual monochromatic spectral (VMS) and conventional polychromatic 120-kVp images obtained during the same abdominal computed tomography (CT) examination and among images reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and model-based iterative reconstruction (MBIR). Our institutional review board approved this prospective study; each participant provided written informed consent. Thirty-one patients (19 men, 12 women; age range, 59–85 years; mean age, 73.2 ± 5.5 years) with renal cysts underwent unenhanced 120-kVp CT followed by sequential fast kVp-switching dual-energy (80/140 kVp) and 120-kVp abdominal enhanced CT in the nephrographic phase over a 10-cm scan length with a random acquisition order and 4.5-second intervals. Fifty-one renal cysts (maximal diameter, 18.0 ± 14.7 mm [range, 4–61 mm]) were identified. The CT attenuation values of the cysts as well as of the kidneys were measured on the unenhanced images, enhanced VMS images (at 70 keV) reconstructed using FBP and ASIR from dual-energy data, and enhanced 120-kVp images reconstructed using FBP, ASIR, and MBIR. The results were analyzed using the mixed-effects model and paired t test with Bonferroni correction. The attenuation increases (pseudoenhancement) of the renal cysts on the VMS images reconstructed using FBP/ASIR (least square mean, 5.0/6.0 Hounsfield units [HU]; 95% confidence interval, 2.6–7.4/3.6–8.4 HU) were significantly lower than those on the conventional 120-kVp images reconstructed using FBP/ASIR/MBIR (least square mean, 12.1/12.8/11.8 HU; 95% confidence interval, 9.8–14.5/10.4–15.1/9.4–14.2 HU) (all P < .001); on the other hand, the CT attenuation values of the kidneys on the VMS images were comparable to those on the 120-kVp images. Regardless of the reconstruction algorithm, 70-keV VMS images showed
Bias-limited extraction of cosmological parameters
Energy Technology Data Exchange (ETDEWEB)
Shimon, Meir; Itzhaki, Nissan; Rephaeli, Yoel, E-mail: meirs@wise.tau.ac.il, E-mail: nitzhaki@post.tau.ac.il, E-mail: yoelr@wise.tau.ac.il [School of Physics and Astronomy, Tel Aviv University, Tel Aviv 69978 (Israel)
2013-03-01
It is known that modeling uncertainties and astrophysical foregrounds can potentially introduce appreciable bias in the deduced values of cosmological parameters. While it is commonly assumed that these uncertainties will be accounted for to a sufficient level of precision, the level of bias has not been properly quantified in most cases of interest. We show that the requirement that the bias in derived values of cosmological parameters does not surpass nominal statistical error, translates into a maximal level of overall error O(N{sup −½}) on |ΔP(k)|/P(k) and |ΔC{sub l}|/C{sub l}, where P(k), C{sub l}, and N are the matter power spectrum, angular power spectrum, and number of (independent Fourier) modes at a given scale l or k probed by the cosmological survey, respectively. This required level has important consequences on the precision with which cosmological parameters are hoped to be determined by future surveys: in virtually all ongoing and near future surveys N typically falls in the range 10{sup 6}−10{sup 9}, implying that the required overall theoretical modeling and numerical precision is already very high. Future redshifted-21-cm observations, projected to sample ∼ 10{sup 14} modes, will require knowledge of the matter power spectrum to a fantastic 10{sup −7} precision level. We conclude that realizing the expected potential of future cosmological surveys, which aim at detecting 10{sup 6}−10{sup 14} modes, sets the formidable challenge of reducing the overall level of uncertainty to 10{sup −3}−10{sup −7}.
News Consumption and Media Bias
Yi Xiang; Miklos Sarvary
2007-01-01
Bias in the market for news is well-documented. Recent research in economics explains the phenomenon by assuming that consumers want to read (watch) news that is consistent with their tastes or prior beliefs rather than the truth. The present paper builds on this idea but recognizes that (i) besides “biased” consumers, there are also “conscientious” consumers whose sole interest is in discovering the truth, and (ii) consistent with reality, media bias is constrained by the truth. These two fa...
The coalitional value theory of antigay bias
Winegard, Bo; Reynolds, Tania; Baumeister, Roy F.; Plant, E. Ashby
2016-01-01
Research indicates that antigay bias follows a specific pattern (and probably has throughout written history, at least in the West): (a) men evince more antigay bias than women; (b) men who belong to traditionally male coalitions evince more antigay bias than those who do not; (c) antigay bias is
Morsanyi, Kinga; Primi, Caterina; Chiesi, Francesca; Handley, Simon
2009-01-01
In three studies we looked at two typical misconceptions of probability: the representativeness heuristic, and the equiprobability bias. The literature on statistics education predicts that some typical errors and biases (e.g., the equiprobability bias) increase with education, whereas others decrease. This is in contrast with reasoning theorists'…
EVALUATING GENDER-BIAS IN THE IRANIAN PRE-UNIVERSITY ENGLISH TEXTBOOKS
Directory of Open Access Journals (Sweden)
Ali Roohani
2013-07-01
Full Text Available Abstract: Textbooks can affect learners’ attitudes, viewpoints, and their choice of language in second/foreign language (L2 communication. The various ways in which the people are displayed in communication may affect students’ viewpoints. This study was an attempt to examine several potential areas of gender-bias in the representation of women and men in the pre-university English textbook, an English language teaching (ELT textbook with two volumes taught in the high schools of Iran. To evaluate this textbook, content analysis was done in terms of gender-bias, gender-neutral, male-generics, and the firstness in the reading texts, instructions, exercises and illustrations. The frequency and percentages of names, nouns, pronouns and pictures attributed to each gender (i.e., males and females were obtained and chi-square tests were carried out. In general, names, nouns and pictures pertinent to males outnumbered those attributed to females. Besides, there was a statistically significant difference between males and females in the two volumes of the pre-university textbook in terms of the above features. Also, male-oriented terms came first more frequently. However, there was not a statistically significant difference between male and female pronouns between the two volumes, though the percentage of male pronouns was higher. Moreover, the textbook included many gender-neutral nouns and pronouns not having any gender orientations. Findings indicated that the Iranian pre-university English textbook was somehow male-oriented and gender-biased as regards names, nouns, firstness and pictures associated with them though great efforts were made to avoid specific gender orientations.
Survivor bias in Mendelian randomization analysis
DEFF Research Database (Denmark)
Vansteelandt, Stijn; Dukes, Oliver; Martinussen, Torben
2017-01-01
Mendelian randomization studies employ genotypes as experimental handles to infer the effect of genetically modified exposures (e.g. vitamin D exposure) on disease outcomes (e.g. mortality). The statistical analysis of these studies makes use of the standard instrumental variables framework. Many...... of these studies focus on elderly populations, thereby ignoring the problem of left truncation, which arises due to the selection of study participants being conditional upon surviving up to the time of study onset. Such selection, in general, invalidates the assumptions on which the instrumental variables...... analysis rests. We show that Mendelian randomization studies of adult or elderly populations will therefore, in general, return biased estimates of the exposure effect when the considered genotype affects mortality; in contrast, standard tests of the causal null hypothesis that the exposure does not affect...
Information filtering via biased heat conduction
Liu, Jian-Guo; Zhou, Tao; Guo, Qiang
2011-09-01
The process of heat conduction has recently found application in personalized recommendation [Zhou , Proc. Natl. Acad. Sci. USA PNASA60027-842410.1073/pnas.1000488107107, 4511 (2010)], which is of high diversity but low accuracy. By decreasing the temperatures of small-degree objects, we present an improved algorithm, called biased heat conduction, which could simultaneously enhance the accuracy and diversity. Extensive experimental analyses demonstrate that the accuracy on MovieLens, Netflix, and Delicious datasets could be improved by 43.5%, 55.4% and 19.2%, respectively, compared with the standard heat conduction algorithm and also the diversity is increased or approximately unchanged. Further statistical analyses suggest that the present algorithm could simultaneously identify users' mainstream and special tastes, resulting in better performance than the standard heat conduction algorithm. This work provides a creditable way for highly efficient information filtering.
Statistical modeling for degradation data
Lio, Yuhlong; Ng, Hon; Tsai, Tzong-Ru
2017-01-01
This book focuses on the statistical aspects of the analysis of degradation data. In recent years, degradation data analysis has come to play an increasingly important role in different disciplines such as reliability, public health sciences, and finance. For example, information on products’ reliability can be obtained by analyzing degradation data. In addition, statistical modeling and inference techniques have been developed on the basis of different degradation measures. The book brings together experts engaged in statistical modeling and inference, presenting and discussing important recent advances in degradation data analysis and related applications. The topics covered are timely and have considerable potential to impact both statistics and reliability engineering.
USING STATISTICAL SURVEY IN ECONOMICS
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Delia TESELIOS
2012-01-01
Full Text Available Statistical survey is an effective method of statistical investigation that involves gathering quantitative data, which is often preferred in statistical reports due to the information which can be obtained regarding the entire population studied by observing a part of it. Therefore, because of the information provided, polls are used in many research areas. In economics, statistics are used in the decision making process in choosing competitive strategies in the analysis of certain economic phenomena, the formulation of forecasts. Economic study presented in this paper is to illustrate how a simple random sampling is used to analyze the existing parking spaces situation in a given locality.
Biased Brownian dynamics for rate constant calculation.
Zou, G; Skeel, R D; Subramaniam, S
2000-01-01
An enhanced sampling method-biased Brownian dynamics-is developed for the calculation of diffusion-limited biomolecular association reaction rates with high energy or entropy barriers. Biased Brownian dynamics introduces a biasing force in addition to the electrostatic force between the reactants, and it associates a probability weight with each trajectory. A simulation loses weight when movement is along the biasing force and gains weight when movement is against the biasing force. The sampl...
Exploring Attribution Theory and Bias
Robinson, Jessica A.
2017-01-01
Courses: This activity can be used in a wide range of classes, including interpersonal communication, introduction to communication, and small group communication. Objectives: After completing this activity, students should be able to: (1) define attribution theory, personality attribution, situational attribution, and attribution bias; (2)…
Ratio Bias and Policy Preferences
DEFF Research Database (Denmark)
Pedersen, Rasmus Tue
2016-01-01
Numbers permeate modern political communication. While current scholarship on framing effects has focused on the persuasive effects of words and arguments, this article shows that framing of numbers can also substantially affect policy preferences. Such effects are caused by ratio bias, which...
Bias in Peripheral Depression Biomarkers
DEFF Research Database (Denmark)
Carvalho, André F; Köhler, Cristiano A; Brunoni, André R
2016-01-01
BACKGROUND: To aid in the differentiation of individuals with major depressive disorder (MDD) from healthy controls, numerous peripheral biomarkers have been proposed. To date, no comprehensive evaluation of the existence of bias favoring the publication of significant results or inflating effect...
International Nuclear Information System (INIS)
Kwee, Regina
2010-01-01
Since the restart of the LHC in November 2009, ATLAS has collected inelastic pp collisions to perform first measurements on charged particle densities. These measurements will help to constrain various models describing phenomenologically soft parton interactions. Understanding the trigger efficiencies for different event types are therefore crucial to minimize any possible bias in the event selection. ATLAS uses two main minimum bias triggers, featuring complementary detector components and trigger levels. While a hardware based first trigger level situated in the forward regions with 2.2 < |η| < 3.8 has been proven to select pp-collisions very efficiently, the Inner Detector based minimum bias trigger uses a random seed on filled bunches and central tracking detectors for the event selection. Both triggers were essential for the analysis of kinematic spectra of charged particles. Their performance and trigger efficiency measurements as well as studies on possible bias sources will be presented. We also highlight the advantage of these triggers for particle correlation analyses. (author)
Gender bias in teaching evaluations
Mengel, Friederike; Sauermann, Jan; Zölitz, Ulf Zoelitz
2017-01-01
This paper provides new evidence on gender bias in teaching evaluations. We exploit a quasi-experimental dataset of 19,952 student evaluations of university faculty in a context where students are randomly allocated to female or male instructors. Despite the fact that neither students’ grades nor
Attentional Bias in Math Anxiety
Directory of Open Access Journals (Sweden)
Orly eRubinsten
2015-10-01
Full Text Available Cognitive theory from the field of general anxiety suggests that the tendency to display attentional bias toward negative information results in anxiety. Accordingly, the current study aims to investigate whether attentional bias is involved in math anxiety as well (i.e., a persistent negative reaction to math. Twenty seven participants (14 with high levels of math anxiety and 13 with low levels of math anxiety were presented with a novel computerized numerical version of the well established dot probe task. One of 6 types of prime stimuli, either math related or typically neutral, were presented on one side of a computer screen. The prime was preceded by a probe (either one or two asterisks that appeared in either the prime or the opposite location. Participants had to discriminate probe identity (one or two asterisks. Math anxious individuals reacted faster when the probe was at the location of the numerical related stimuli. This suggests the existence of attentional bias in math anxiety. That is, for math anxious individuals, the cognitive system selectively favored the processing of emotionally negative information (i.e., math related words. These findings suggest that attentional bias is linked to unduly intense math anxiety symptoms.
Attentional bias in math anxiety.
Rubinsten, Orly; Eidlin, Hili; Wohl, Hadas; Akibli, Orly
2015-01-01
Cognitive theory from the field of general anxiety suggests that the tendency to display attentional bias toward negative information results in anxiety. Accordingly, the current study aims to investigate whether attentional bias is involved in math anxiety (MA) as well (i.e., a persistent negative reaction to math). Twenty seven participants (14 with high levels of MA and 13 with low levels of MA) were presented with a novel computerized numerical version of the well established dot probe task. One of six types of prime stimuli, either math related or typically neutral, was presented on one side of a computer screen. The prime was preceded by a probe (either one or two asterisks) that appeared in either the prime or the opposite location. Participants had to discriminate probe identity (one or two asterisks). Math anxious individuals reacted faster when the probe was at the location of the numerical related stimuli. This suggests the existence of attentional bias in MA. That is, for math anxious individuals, the cognitive system selectively favored the processing of emotionally negative information (i.e., math related words). These findings suggest that attentional bias is linked to unduly intense MA symptoms.
Perception bias in route choice
Vreeswijk, Jacob Dirk; Thomas, Tom; van Berkum, Eric C.; van Arem, Bart
2014-01-01
Travel time is probably one of the most studied attributes in route choice. Recently, perception of travel time received more attention as several studies have shown its importance in explaining route choice behavior. In particular, travel time estimates by travelers appear to be biased against
Biased sampling, over-identified parameter problems and beyond
Qin, Jing
2017-01-01
This book is devoted to biased sampling problems (also called choice-based sampling in Econometrics parlance) and over-identified parameter estimation problems. Biased sampling problems appear in many areas of research, including Medicine, Epidemiology and Public Health, the Social Sciences and Economics. The book addresses a range of important topics, including case and control studies, causal inference, missing data problems, meta-analysis, renewal process and length biased sampling problems, capture and recapture problems, case cohort studies, exponential tilting genetic mixture models etc. The goal of this book is to make it easier for Ph. D students and new researchers to get started in this research area. It will be of interest to all those who work in the health, biological, social and physical sciences, as well as those who are interested in survey methodology and other areas of statistical science, among others. .
Correction of stream quality trends for the effects of laboratory measurement bias
Alexander, Richard B.; Smith, Richard A.; Schwarz, Gregory E.
1993-01-01
We present a statistical model relating measurements of water quality to associated errors in laboratory methods. Estimation of the model allows us to correct trends in water quality for long-term and short-term variations in laboratory measurement errors. An illustration of the bias correction method for a large national set of stream water quality and quality assurance data shows that reductions in the bias of estimates of water quality trend slopes are achieved at the expense of increases in the variance of these estimates. Slight improvements occur in the precision of estimates of trend in bias by using correlative information on bias and water quality to estimate random variations in measurement bias. The results of this investigation stress the need for reliable, long-term quality assurance data and efficient statistical methods to assess the effects of measurement errors on the detection of water quality trends.
Bias in the physical examination of patients with lumbar radiculopathy
Directory of Open Access Journals (Sweden)
Katz Jeffrey N
2010-11-01
Full Text Available Abstract Background No prior studies have examined systematic bias in the musculoskeletal physical examination. The objective of this study was to assess the effects of bias due to prior knowledge of lumbar spine magnetic resonance imaging findings (MRI on perceived diagnostic accuracy of the physical examination for lumbar radiculopathy. Methods This was a cross-sectional comparison of the performance characteristics of the physical examination with blinding to MRI results (the 'independent group' with performance in the situation where the physical examination was not blinded to MRI results (the 'non-independent group'. The reference standard was the final diagnostic impression of nerve root impingement by the examining physician. Subjects were recruited from a hospital-based outpatient specialty spine clinic. All adults age 18 and older presenting with lower extremity radiating pain of duration ≤ 12 weeks were evaluated for participation. 154 consecutively recruited subjects with lumbar disk herniation confirmed by lumbar spine MRI were included in this study. Sensitivities and specificities with 95% confidence intervals were calculated in the independent and non-independent groups for the four components of the radiculopathy examination: 1 provocative testing, 2 motor strength testing, 3 pinprick sensory testing, and 4 deep tendon reflex testing. Results The perceived sensitivity of sensory testing was higher with prior knowledge of MRI results (20% vs. 36%; p = 0.05. Sensitivities and specificities for exam components otherwise showed no statistically significant differences between groups. Conclusions Prior knowledge of lumbar MRI results may introduce bias into the pinprick sensory testing component of the physical examination for lumbar radiculopathy. No statistically significant effect of bias was seen for other components of the physical examination. The effect of bias due to prior knowledge of lumbar MRI results should be considered
Bias in the physical examination of patients with lumbar radiculopathy
2010-01-01
Background No prior studies have examined systematic bias in the musculoskeletal physical examination. The objective of this study was to assess the effects of bias due to prior knowledge of lumbar spine magnetic resonance imaging findings (MRI) on perceived diagnostic accuracy of the physical examination for lumbar radiculopathy. Methods This was a cross-sectional comparison of the performance characteristics of the physical examination with blinding to MRI results (the 'independent group') with performance in the situation where the physical examination was not blinded to MRI results (the 'non-independent group'). The reference standard was the final diagnostic impression of nerve root impingement by the examining physician. Subjects were recruited from a hospital-based outpatient specialty spine clinic. All adults age 18 and older presenting with lower extremity radiating pain of duration ≤ 12 weeks were evaluated for participation. 154 consecutively recruited subjects with lumbar disk herniation confirmed by lumbar spine MRI were included in this study. Sensitivities and specificities with 95% confidence intervals were calculated in the independent and non-independent groups for the four components of the radiculopathy examination: 1) provocative testing, 2) motor strength testing, 3) pinprick sensory testing, and 4) deep tendon reflex testing. Results The perceived sensitivity of sensory testing was higher with prior knowledge of MRI results (20% vs. 36%; p = 0.05). Sensitivities and specificities for exam components otherwise showed no statistically significant differences between groups. Conclusions Prior knowledge of lumbar MRI results may introduce bias into the pinprick sensory testing component of the physical examination for lumbar radiculopathy. No statistically significant effect of bias was seen for other components of the physical examination. The effect of bias due to prior knowledge of lumbar MRI results should be considered when an isolated
Bias-dependent hybrid PKI empirical-neural model of microwave FETs
Marinković, Zlatica; Pronić-Rančić, Olivera; Marković, Vera
2011-10-01
Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical-neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.
Cao, Juliang; Cai, Shaokun; Wu, Meiping; Lian, Junxiang
2018-01-01
Compensation of gravity disturbance can improve the precision of inertial navigation, but the effect of compensation will decrease due to the accelerometer bias, and estimation of the accelerometer bias is a crucial issue in gravity disturbance compensation. This paper first investigates the effect of accelerometer bias on gravity disturbance compensation, and the situation in which the accelerometer bias should be estimated is established. The accelerometer bias is estimated from the gravity vector measurement, and a model of measurement noise in gravity vector measurement is built. Based on this model, accelerometer bias is separated from the gravity vector measurement error by the method of least squares. Horizontal gravity disturbances are calculated through EGM2008 spherical harmonic model to build the simulation scene, and the simulation results indicate that precise estimations of the accelerometer bias can be obtained with the proposed method. PMID:29547552
Tie, Junbo; Cao, Juliang; Chang, Lubing; Cai, Shaokun; Wu, Meiping; Lian, Junxiang
2018-03-16
Compensation of gravity disturbance can improve the precision of inertial navigation, but the effect of compensation will decrease due to the accelerometer bias, and estimation of the accelerometer bias is a crucial issue in gravity disturbance compensation. This paper first investigates the effect of accelerometer bias on gravity disturbance compensation, and the situation in which the accelerometer bias should be estimated is established. The accelerometer bias is estimated from the gravity vector measurement, and a model of measurement noise in gravity vector measurement is built. Based on this model, accelerometer bias is separated from the gravity vector measurement error by the method of least squares. Horizontal gravity disturbances are calculated through EGM2008 spherical harmonic model to build the simulation scene, and the simulation results indicate that precise estimations of the accelerometer bias can be obtained with the proposed method.
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Smokers exhibit biased neural processing of smoking and affective images.
Oliver, Jason A; Jentink, Kade G; Drobes, David J; Evans, David E
2016-08-01
There has been growing interest in the role that implicit processing of drug cues can play in motivating drug use behavior. However, the extent to which drug cue processing biases relate to the processing biases exhibited to other types of evocative stimuli is largely unknown. The goal of the present study was to determine how the implicit cognitive processing of smoking cues relates to the processing of affective cues using a novel paradigm. Smokers (n = 50) and nonsmokers (n = 38) completed a picture-viewing task, in which participants were presented with a series of smoking, pleasant, unpleasant, and neutral images while engaging in a distractor task designed to direct controlled resources away from conscious processing of image content. Electroencephalogram recordings were obtained throughout the task for extraction of event-related potentials (ERPs). Smokers exhibited differential processing of smoking cues across 3 different ERP indices compared with nonsmokers. Comparable effects were found for pleasant cues on 2 of these indices. Late cognitive processing of smoking and pleasant cues was associated with nicotine dependence and cigarette use. Results suggest that cognitive biases may extend across classes of stimuli among smokers. This raises important questions about the fundamental meaning of cognitive biases, and suggests the need to consider generalized cognitive biases in theories of drug use behavior and interventions based on cognitive bias modification. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Statistics in the pharmacy literature.
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.
Self-assessed performance improves statistical fusion of image labels
International Nuclear Information System (INIS)
Bryan, Frederick W.; Xu, Zhoubing; Asman, Andrew J.; Allen, Wade M.; Reich, Daniel S.; Landman, Bennett A.
2014-01-01
Purpose: Expert manual labeling is the gold standard for image segmentation, but this process is difficult, time-consuming, and prone to inter-individual differences. While fully automated methods have successfully targeted many anatomies, automated methods have not yet been developed for numerous essential structures (e.g., the internal structure of the spinal cord as seen on magnetic resonance imaging). Collaborative labeling is a new paradigm that offers a robust alternative that may realize both the throughput of automation and the guidance of experts. Yet, distributing manual labeling expertise across individuals and sites introduces potential human factors concerns (e.g., training, software usability) and statistical considerations (e.g., fusion of information, assessment of confidence, bias) that must be further explored. During the labeling process, it is simple to ask raters to self-assess the confidence of their labels, but this is rarely done and has not been previously quantitatively studied. Herein, the authors explore the utility of self-assessment in relation to automated assessment of rater performance in the context of statistical fusion. Methods: The authors conducted a study of 66 volumes manually labeled by 75 minimally trained human raters recruited from the university undergraduate population. Raters were given 15 min of training during which they were shown examples of correct segmentation, and the online segmentation tool was demonstrated. The volumes were labeled 2D slice-wise, and the slices were unordered. A self-assessed quality metric was produced by raters for each slice by marking a confidence bar superimposed on the slice. Volumes produced by both voting and statistical fusion algorithms were compared against a set of expert segmentations of the same volumes. Results: Labels for 8825 distinct slices were obtained. Simple majority voting resulted in statistically poorer performance than voting weighted by self-assessed performance
Self-assessed performance improves statistical fusion of image labels
Energy Technology Data Exchange (ETDEWEB)
Bryan, Frederick W., E-mail: frederick.w.bryan@vanderbilt.edu; Xu, Zhoubing; Asman, Andrew J.; Allen, Wade M. [Electrical Engineering, Vanderbilt University, Nashville, Tennessee 37235 (United States); Reich, Daniel S. [Translational Neuroradiology Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892 (United States); Landman, Bennett A. [Electrical Engineering, Vanderbilt University, Nashville, Tennessee 37235 (United States); Biomedical Engineering, Vanderbilt University, Nashville, Tennessee 37235 (United States); and Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tennessee 37235 (United States)
2014-03-15
Purpose: Expert manual labeling is the gold standard for image segmentation, but this process is difficult, time-consuming, and prone to inter-individual differences. While fully automated methods have successfully targeted many anatomies, automated methods have not yet been developed for numerous essential structures (e.g., the internal structure of the spinal cord as seen on magnetic resonance imaging). Collaborative labeling is a new paradigm that offers a robust alternative that may realize both the throughput of automation and the guidance of experts. Yet, distributing manual labeling expertise across individuals and sites introduces potential human factors concerns (e.g., training, software usability) and statistical considerations (e.g., fusion of information, assessment of confidence, bias) that must be further explored. During the labeling process, it is simple to ask raters to self-assess the confidence of their labels, but this is rarely done and has not been previously quantitatively studied. Herein, the authors explore the utility of self-assessment in relation to automated assessment of rater performance in the context of statistical fusion. Methods: The authors conducted a study of 66 volumes manually labeled by 75 minimally trained human raters recruited from the university undergraduate population. Raters were given 15 min of training during which they were shown examples of correct segmentation, and the online segmentation tool was demonstrated. The volumes were labeled 2D slice-wise, and the slices were unordered. A self-assessed quality metric was produced by raters for each slice by marking a confidence bar superimposed on the slice. Volumes produced by both voting and statistical fusion algorithms were compared against a set of expert segmentations of the same volumes. Results: Labels for 8825 distinct slices were obtained. Simple majority voting resulted in statistically poorer performance than voting weighted by self-assessed performance
Booth, Charlotte; Songco, Annabel; Parsons, Sam; Heathcote, Lauren; Vincent, John; Keers, Robert; Fox, Elaine
2017-12-29
Optimal psychological development is dependent upon a complex interplay between individual and situational factors. Investigating the development of these factors in adolescence will help to improve understanding of emotional vulnerability and resilience. The CogBIAS longitudinal study (CogBIAS-L-S) aims to combine cognitive and genetic approaches to investigate risk and protective factors associated with the development of mood and impulsivity-related outcomes in an adolescent sample. CogBIAS-L-S is a three-wave longitudinal study of typically developing adolescents conducted over 4 years, with data collection at age 12, 14 and 16. At each wave participants will undergo multiple assessments including a range of selective cognitive processing tasks (e.g. attention bias, interpretation bias, memory bias) and psychological self-report measures (e.g. anxiety, depression, resilience). Saliva samples will also be collected at the baseline assessment for genetic analyses. Multilevel statistical analyses will be performed to investigate the developmental trajectory of cognitive biases on psychological functioning, as well as the influence of genetic moderation on these relationships. CogBIAS-L-S represents the first longitudinal study to assess multiple cognitive biases across adolescent development and the largest study of its kind to collect genetic data. It therefore provides a unique opportunity to understand how genes and the environment influence the development and maintenance of cognitive biases and provide insight into risk and protective factors that may be key targets for intervention.
... 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 ...
State Transportation Statistics 2014
2014-12-15
The Bureau of Transportation Statistics (BTS) presents State Transportation Statistics 2014, a statistical profile of transportation in the 50 states and the District of Columbia. This is the 12th annual edition of State Transportation Statistics, a ...
Scaling of the first-passage time of biased diffusion on hierarchical comb structures
International Nuclear Information System (INIS)
Lin Zhifang; Tao Ruibao.
1989-12-01
Biased diffusion on hierarchical comb structures is studied within an exact renormalization group scheme. The scaling exponents of the moments of the first-passage time for random walks are obtained. It is found that the scaling properties of the diffusion depend only on the direction of bias. In this particular case, the presence of bias may give rise to a new multifractality. (author). 7 refs, 2 figs
International Nuclear Information System (INIS)
Colbeck, Roger; Kent, Adrian
2006-01-01
Alice is a charismatic quantum cryptographer who believes her parties are unmissable; Bob is a (relatively) glamorous string theorist who believes he is an indispensable guest. To prevent possibly traumatic collisions of self-perception and reality, their social code requires that decisions about invitation or acceptance be made via a cryptographically secure variable-bias coin toss (VBCT). This generates a shared random bit by the toss of a coin whose bias is secretly chosen, within a stipulated range, by one of the parties; the other party learns only the random bit. Thus one party can secretly influence the outcome, while both can save face by blaming any negative decisions on bad luck. We describe here some cryptographic VBCT protocols whose security is guaranteed by quantum theory and the impossibility of superluminal signaling, setting our results in the context of a general discussion of secure two-party computation. We also briefly discuss other cryptographic applications of VBCT
Probability biases as Bayesian inference
Directory of Open Access Journals (Sweden)
Andre; C. R. Martins
2006-11-01
Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.
Colbeck, Roger; Kent, Adrian
2006-03-01
Alice is a charismatic quantum cryptographer who believes her parties are unmissable; Bob is a (relatively) glamorous string theorist who believes he is an indispensable guest. To prevent possibly traumatic collisions of self-perception and reality, their social code requires that decisions about invitation or acceptance be made via a cryptographically secure variable-bias coin toss (VBCT). This generates a shared random bit by the toss of a coin whose bias is secretly chosen, within a stipulated range, by one of the parties; the other party learns only the random bit. Thus one party can secretly influence the outcome, while both can save face by blaming any negative decisions on bad luck. We describe here some cryptographic VBCT protocols whose security is guaranteed by quantum theory and the impossibility of superluminal signaling, setting our results in the context of a general discussion of secure two-party computation. We also briefly discuss other cryptographic applications of VBCT.
Automated statistical modeling of analytical measurement systems
International Nuclear Information System (INIS)
Jacobson, J.J.
1992-01-01
The statistical modeling of analytical measurement systems at the Idaho Chemical Processing Plant (ICPP) has been completely automated through computer software. The statistical modeling of analytical measurement systems is one part of a complete quality control program used by the Remote Analytical Laboratory (RAL) at the ICPP. The quality control program is an integration of automated data input, measurement system calibration, database management, and statistical process control. The quality control program and statistical modeling program meet the guidelines set forth by the American Society for Testing Materials and American National Standards Institute. A statistical model is a set of mathematical equations describing any systematic bias inherent in a measurement system and the precision of a measurement system. A statistical model is developed from data generated from the analysis of control standards. Control standards are samples which are made up at precise known levels by an independent laboratory and submitted to the RAL. The RAL analysts who process control standards do not know the values of those control standards. The object behind statistical modeling is to describe real process samples in terms of their bias and precision and, to verify that a measurement system is operating satisfactorily. The processing of control standards gives us this ability
Chowdhry, D P
1995-01-01
This article identifies gender bias against female children and youth in India. Gender bias is based on centuries-old religious beliefs and sayings from ancient times. Discrimination is reflected in denial or ignorance of female children's educational, health, nutrition, and recreational needs. Female infanticide and selective abortion of female fetuses are other forms of discrimination. The task of eliminating or reducing gender bias will involve legal, developmental, political, and administrative measures. Public awareness needs to be created. There is a need to reorient the education and health systems and to advocate for gender equality. The government of India set the following goals for the 1990s: to protect the survival of the girl child and practice safe motherhood; to develop the girl child in general; and to protect vulnerable girl children in different circumstances and in special groups. The Health Authorities should monitor the laws carefully to assure marriage after the minimum age, ban sex determination of the fetus, and monitor the health and nutrition of pre-school girls and nursing and pregnant mothers. Mothers need to be encouraged to breast feed, and to breast feed equally between genders. Every village and slum area needs a mini health center. Maternal mortality must decline. Primary health centers and hospitals need more women's wards. Education must be universally accessible. Enrollments should be increased by educating rural tribal and slum parents, reducing distances between home and school, making curriculum more relevant to girls, creating more female teachers, and providing facilities and incentives for meeting the needs of girl students. Supplementary income could be provided to families for sending girls to school. Recreational activities must be free of gender bias. Dowry, sati, and devdasi systems should be banned.
Competition and Commercial Media Bias
Blasco, Andrea; Sobbrio, Francesco
2011-01-01
This paper reviews the empirical evidence on commercial media bias (i.e., advertisers influence over media accuracy) and then introduces a simple model to summarize the main elements of the theoretical literature. The analysis provides three main policy insights for media regulators: i) Media regulators should target their monitoring efforts towards news contents upon which advertisers are likely to share similar preferences; ii) In advertising industries characterized by high correlation in ...
BEHAVIORAL BIASES IN TRADING SECURITIES
Directory of Open Access Journals (Sweden)
Turcan Ciprian Sebastian
2010-12-01
Full Text Available The main thesis of this paper represents the importance and the effects that human behavior has over capital markets. It is important to see the link between the asset valuation and investor sentiment that motivate to pay for an asset a certain prices over/below the intrinsic value. The main behavioral aspects discussed are emotional factors such as: fear of regret, overconfidence, perseverance, loss aversion ,heuristic biases, misinformation and thinking errors, herding and their consequences.
Significant biases affecting abundance determinations
Wesson, Roger
2015-08-01
I have developed two highly efficient codes to automate analyses of emission line nebulae. The tools place particular emphasis on the propagation of uncertainties. The first tool, ALFA, uses a genetic algorithm to rapidly optimise the parameters of gaussian fits to line profiles. It can fit emission line spectra of arbitrary resolution, wavelength range and depth, with no user input at all. It is well suited to highly multiplexed spectroscopy such as that now being carried out with instruments such as MUSE at the VLT. The second tool, NEAT, carries out a full analysis of emission line fluxes, robustly propagating uncertainties using a Monte Carlo technique.Using these tools, I have found that considerable biases can be introduced into abundance determinations if the uncertainty distribution of emission lines is not well characterised. For weak lines, normally distributed uncertainties are generally assumed, though it is incorrect to do so, and significant biases can result. I discuss observational evidence of these biases. The two new codes contain routines to correctly characterise the probability distributions, giving more reliable results in analyses of emission line nebulae.
Galaxy formation and physical bias
Cen, Renyue; Ostriker, Jeremiah P.
1992-01-01
We have supplemented our code, which computes the evolution of the physical state of a representative piece of the universe to include, not only the dynamics of dark matter (with a standard PM code), and the hydrodynamics of the gaseous component (including detailed collisional and radiative processes), but also galaxy formation on a heuristic but plausible basis. If, within a cell the gas is Jeans' unstable, collapsing, and cooling rapidly, it is transformed to galaxy subunits, which are then followed with a collisionless code. After grouping them into galaxies, we estimate the relative distributions of galaxies and dark matter and the relative velocities of galaxies and dark matter. In a large scale CDM run of 80/h Mpc size with 8 x 10 exp 6 cells and dark matter particles, we find that physical bias b is on the 8/h Mpc scale is about 1.6 and increases towards smaller scales, and that velocity bias is about 0.8 on the same scale. The comparable HDM simulation is highly biased with b = 2.7 on the 8/h Mpc scale. Implications of these results are discussed in the light of the COBE observations which provide an accurate normalization for the initial power spectrum. CDM can be ruled out on the basis of too large a predicted small scale velocity dispersion at greater than 95 percent confidence level.
Opinion dynamics with confirmation bias.
Directory of Open Access Journals (Sweden)
Armen E Allahverdyan
Full Text Available Confirmation bias is the tendency to acquire or evaluate new information in a way that is consistent with one's preexisting beliefs. It is omnipresent in psychology, economics, and even scientific practices. Prior theoretical research of this phenomenon has mainly focused on its economic implications possibly missing its potential connections with broader notions of cognitive science.We formulate a (non-Bayesian model for revising subjective probabilistic opinion of a confirmationally-biased agent in the light of a persuasive opinion. The revision rule ensures that the agent does not react to persuasion that is either far from his current opinion or coincides with it. We demonstrate that the model accounts for the basic phenomenology of the social judgment theory, and allows to study various phenomena such as cognitive dissonance and boomerang effect. The model also displays the order of presentation effect-when consecutively exposed to two opinions, the preference is given to the last opinion (recency or the first opinion (primacy -and relates recency to confirmation bias. Finally, we study the model in the case of repeated persuasion and analyze its convergence properties.The standard Bayesian approach to probabilistic opinion revision is inadequate for describing the observed phenomenology of persuasion process. The simple non-Bayesian model proposed here does agree with this phenomenology and is capable of reproducing a spectrum of effects observed in psychology: primacy-recency phenomenon, boomerang effect and cognitive dissonance. We point out several limitations of the model that should motivate its future development.
Non-extensive statistical mechanics and black hole entropy from quantum geometry
Directory of Open Access Journals (Sweden)
Abhishek Majhi
2017-12-01
Full Text Available Using non-extensive statistical mechanics, the BekensteinâHawking area law is obtained from microstates of black holes in loop quantum gravity, for arbitrary real positive values of the BarberoâImmirzi parameter (Î³. The arbitrariness of Î³ is encoded in the strength of the âbiasâ created in the horizon microstates through the coupling with the quantum geometric fields exterior to the horizon. An experimental determination of Î³ will fix this coupling, leaving out the macroscopic area of the black hole to be the only free quantity of the theory.
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.
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 ...
Matrilateral Bias in Human Grandmothering
Directory of Open Access Journals (Sweden)
Martin Daly
2017-09-01
Full Text Available Children receive more care and resources from their maternal grandmothers than from their paternal grandmothers. This asymmetry is the “matrilateral bias” in grandmaternal investment. Here, we synopsize the evolutionary theories that predict such a bias, and review evidence of its cross-cultural generality and magnitude. Evolutionists have long maintained that investing in a daughter’s child yields greater fitness returns, on average, than investing in a son’s child because of paternity uncertainty: the son’s putative progeny may have been sired by someone else. Recent theoretical work has identified an additional natural selective basis for the matrilateral bias that may be no less important: supporting grandchildren lightens the load on their mother, increasing her capacity to pursue her fitness in other ways, and if she invests those gains either in her natal relatives or in children of a former or future partner, fitness returns accrue to the maternal, but not the paternal, grandmother. In modern democracies, where kinship is reckoned bilaterally and no postmarital residence norms restrict grandmaternal access to grandchildren, many studies have found large matrilateral biases in contact, childcare, and emotional closeness. In other societies, patrilineal ideology and postmarital residence with the husband’s kin (virilocality might be expected to have produced a patrilateral bias instead, but the available evidence refutes this hypothesis. In hunter-gatherers, regardless of professed norms concerning kinship and residence, mothers get needed help at and after childbirth from their mothers, not their mothers-in-law. In traditional agricultural and pastoral societies, patrilineal and virilocal norms are common, but young mothers still turn to their natal families for crucial help, and several studies have documented benefits, including reduced child mortality, associated with access to maternal, but not paternal, grandmothers. Even
Market Efficiency and Behavioral Biases in the WNBA Betting Market
Directory of Open Access Journals (Sweden)
Rodney J. Paul
2014-04-01
Full Text Available The betting market for the Women’s National Basketball Association (WNBA is a thin financial market, which does not attract much interest from sports bettors. Given these characteristics, it is possible that profitable wagering strategies could exist for informed bettors of the WNBA. Using betting data on the WNBA from 2007–2012, we find that simple betting strategies do not earn statistically significant returns. WNBA bettors are like NBA bettors; however, in that they strongly prefer the best teams, particularly when they are on the road. Despite this clear bias, betting against the most popular public wagers is not found to earn statistically significant profits.
Evidence of significant bias in an elementary random number generator
International Nuclear Information System (INIS)
Borgwaldt, H.; Brandl, V.
1981-03-01
An elementary pseudo random number generator for isotropically distributed unit vectors in 3-dimensional space has ben tested for bias. This generator uses the IBM-suplied routine RANDU and a transparent rejection technique. The tests show clearly that non-randomness in the pseudo random numbers generated by the primary IBM generator leads to bias in the order of 1 percent in estimates obtained from the secondary random number generator. FORTRAN listings of 4 variants of the random number generator called by a simple test programme and output listings are included for direct reference. (orig.) [de
Bias-correction in vector autoregressive models
DEFF Research Database (Denmark)
Engsted, Tom; Pedersen, Thomas Quistgaard
2014-01-01
We analyze the properties of various methods for bias-correcting parameter estimates in both stationary and non-stationary vector autoregressive models. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation study......, we show that when the model is stationary this simple bias formula compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models, the analytical bias formula performs noticeably worse than bootstrapping. Both methods yield a notable...... improvement over ordinary least squares. We pay special attention to the risk of pushing an otherwise stationary model into the non-stationary region of the parameter space when correcting for bias. Finally, we consider a recently proposed reduced-bias weighted least squares estimator, and we find...
Short Communication: Gender Bias and Stigmatization against ...
African Journals Online (AJOL)
Short Communication: Gender Bias and Stigmatization against Women Living with ... In Ethiopia, HIV/AIDS is highly stigmatized due to the fact that sexual ... bias, socio-economic situations and traditional beliefs contribute, individually and in ...
Is there bias in editorial choice? Yes
Moustafa, Khaled
2018-01-01
Nature has recently published a Correspondence claiming the absence of fame biases in the editorial choice. The topic is interesting and deserves a deeper analysis than it was presented because the reported brief analysis and its conclusion are somewhat biased for many reasons, some of them are discussed here. Since the editorial assessment is a form of peer-review, the biases reported on external peer-reviews would, thus, apply to the editorial assessment, too. The biases would be proportion...
Bias-field equalizer for bubble memories
Keefe, G. E.
1977-01-01
Magnetoresistive Perm-alloy sensor monitors bias field required to maintain bubble memory. Sensor provides error signal that, in turn, corrects magnitude of bias field. Error signal from sensor can be used to control magnitude of bias field in either auxiliary set of bias-field coils around permanent magnet field, or current in small coils used to remagnetize permanent magnet by infrequent, short, high-current pulse or short sequence of pulses.
Theory of quantum diffusion in biased semiconductors
Bryksin, V V
2003-01-01
A general theory is developed to describe diffusion phenomena in biased semiconductors and semiconductor superlattices. It is shown that the Einstein relation is not applicable for all field strengths so that the calculation of the field-mediated diffusion coefficient represents a separate task. Two quite different diffusion contributions are identified. The first one disappears when the dipole operator commutes with the Hamiltonian. It plays an essential role in the theory of small polarons. The second contribution is obtained from a quantity that is the solution of a kinetic equation but that cannot be identified with the carrier distribution function. This is in contrast to the drift velocity, which is closely related to the distribution function. A general expression is derived for the quantum diffusion regime, which allows a clear physical interpretation within the hopping picture.
Selection bias and the perils of benchmarking.
Denrell, Jerker
2005-04-01
To find the secrets of business success, what could be more natural than studying successful businesses? In fact, nothing could be more dangerous, warns this Stanford professor. Generalizing from the examples of successful companies is like generalizing about New England weather from data taken only in the summer. That's essentially what businesspeople do when they learn from good examples and what consultants, authors, and researchers do when they study only existing companies or--worse yet--only high-performing companies. They reach conclusions from unrepresentative data samples, falling into the classic statistical trap of selection bias. Drawing on a wealth of case studies, for instance, one researcher concluded that great leaders share two key traits: They persist, often despite initial failures, and they are able to persuade others to join them. But those traits are also the hallmarks of spectacularly unsuccessful entrepreneurs, who must persist in the face of failure to incur large losses and must be able to persuade others to pour their money down the drain. To discover what makes a business successful, then, managers should look at both successes and failures. Otherwise, they will overvalue risky business practices, seeing only those companies that won big and not the ones that lost dismally. They will not be able to tell if their current good fortune stems from smart business practices or if they are actually coasting on past accomplishments or good luck. Fortunately, economists have developed relatively simple tools that can correct for selection bias even when data about failed companies are hard to come by. Success may be inspirational, but managers are more likely to find the secrets of high performance if they give the stories of their competitors'failures as full a hearing as they do the stories of dazzling successes.
Statistical aspects of nuclear structure
International Nuclear Information System (INIS)
Parikh, J.C.
1977-01-01
The statistical properties of energy levels and a statistical approach to transition strengths are discussed in relation to nuclear structure studies at high excitation energies. It is shown that the calculations can be extended to the ground state domain also. The discussion is based on the study of random matrix theory of level density and level spacings, using the Gaussian Orthogonal Ensemble (GOE) concept. The short range and long range correlations are also studied statistically. The polynomial expansion method is used to obtain excitation strengths. (A.K.)
The Accuracy Enhancing Effect of Biasing Cues
W. Vanhouche (Wouter); S.M.J. van Osselaer (Stijn)
2009-01-01
textabstractExtrinsic cues such as price and irrelevant attributes have been shown to bias consumers’ product judgments. Results in this article replicate those findings in pretrial judgments but show that such biasing cues can improve quality judgments at a later point in time. Initially biasing
Biased managers, organizational design, and incentive provision
Moreira, Humberto Ataíde; Costa, Cristiano Machado; Ferreira, Daniel Bernardo Soares
2004-01-01
Rio de Janeiro We model the tradeoff between the balance and the strength of incentives implicit in the choice between hierarchical and matrix organizational structures. We show that managerial biases determine which structure is optimal: hierarchical forms are preferred when biases are low, while matrix structures are preferred when biases are high.
An ANOVA approach for statistical comparisons of brain networks.
Fraiman, Daniel; Fraiman, Ricardo
2018-03-16
The study of brain networks has developed extensively over the last couple of decades. By contrast, techniques for the statistical analysis of these networks are less developed. In this paper, we focus on the statistical comparison of brain networks in a nonparametric framework and discuss the associated detection and identification problems. We tested network differences between groups with an analysis of variance (ANOVA) test we developed specifically for networks. We also propose and analyse the behaviour of a new statistical procedure designed to identify different subnetworks. As an example, we show the application of this tool in resting-state fMRI data obtained from the Human Connectome Project. We identify, among other variables, that the amount of sleep the days before the scan is a relevant variable that must be controlled. Finally, we discuss the potential bias in neuroimaging findings that is generated by some behavioural and brain structure variables. Our method can also be applied to other kind of networks such as protein interaction networks, gene networks or social networks.
Measurement bias of fluid velocity in molecular simulations
International Nuclear Information System (INIS)
Tysanner, Martin W.; Garcia, Alejandro L.
2004-01-01
In molecular simulations of fluid flow, the measurement of mean fluid velocity is considered to be a straightforward computation, yet there is some ambiguity in its definition. We show that in systems far from equilibrium, such as those with large temperature or velocity gradients, two commonly used definitions give slightly different results. Specifically, a bias can arise when computing the mean fluid velocity by measuring the mean particle velocity in a cell and averaging this mean over samples. We show that this bias comes from the correlation of momentum and density fluctuations in non-equilibrium fluids, obtain an analytical expression for predicting it, and discuss what system characteristics (e.g., number of particles per cell, temperature gradients) reduce or magnify the error. The bias has a physical origin so although we demonstrate it by direct simulation Monte Carlo (DSMC) computations, the same effect will be observed with other particle-based simulation methods, such as molecular dynamics and lattice gases
Reduction of density-modification bias by β correction
International Nuclear Information System (INIS)
Skubák, Pavol; Pannu, Navraj S.
2011-01-01
A cross-validation-based method for bias reduction in ‘classical’ iterative density modification of experimental X-ray crystallography maps provides significantly more accurate phase-quality estimates and leads to improved automated model building. Density modification often suffers from an overestimation of phase quality, as seen by escalated figures of merit. A new cross-validation-based method to address this estimation bias by applying a bias-correction parameter ‘β’ to maximum-likelihood phase-combination functions is proposed. In tests on over 100 single-wavelength anomalous diffraction data sets, the method is shown to produce much more reliable figures of merit and improved electron-density maps. Furthermore, significantly better results are obtained in automated model building iterated with phased refinement using the more accurate phase probability parameters from density modification
Moise Famien, Adjoua; Defrance, Dimitri; Sultan, Benjamin; Janicot, Serge; Vrac, Mathieu
2017-04-01
Different CMIP exercises show that the simulations of the future/current temperature and precipitation are complex with a high uncertainty degree. For example, the African monsoon system is not correctly simulated and most of the CMIP5 models underestimate the precipitation. Therefore, Global Climate Models (GCMs) show significant systematic biases that require bias correction before it can be used in impacts studies. Several methods of bias corrections have been developed for several years and are increasingly using more complex statistical methods. The aims of this work is to show the interest of the CDFt (Cumulative Distribution Function transfom (Michelangeli et al.,2009)) method to reduce the data bias from 29 CMIP5 GCMs over Africa and to assess the impact of bias corrected data on crop yields prediction by the end of the 21st century. In this work, we apply the CDFt to daily data covering the period from 1950 to 2099 (Historical and RCP8.5) and we correct the climate variables (temperature, precipitation, solar radiation, wind) by the use of the new daily database from the EU project WATer and global CHange (WATCH) available from 1979 to 2013 as reference data. The performance of the method is assessed in several cases. First, data are corrected based on different calibrations periods and are compared, on one hand, with observations to estimate the sensitivity of the method to the calibration period and, on other hand, with another bias-correction method used in the ISIMIP project. We find that, whatever the calibration period used, CDFt corrects well the mean state of variables and preserves their trend, as well as daily rainfall occurrence and intensity distributions. However, some differences appear when compared to the outputs obtained with the method used in ISIMIP and show that the quality of the correction is strongly related to the reference data. Secondly, we validate the bias correction method with the agronomic simulations (SARRA-H model (Kouressy
Attentional bias mediates the effect of neurostimulation on emotional vulnerability.
Chen, Nigel T M; Basanovic, Julian; Notebaert, Lies; MacLeod, Colin; Clarke, Patrick J F
2017-10-01
Transcranial direct current stimulation (tDCS) is a neuromodulatory technique which has garnered recent interest in the potential treatment for emotion-based psychopathology. While accumulating evidence suggests that tDCS may attenuate emotional vulnerability, critically, little is known about underlying mechanisms of this effect. The present study sought to clarify this by examining the possibility that tDCS may affect emotional vulnerability via its capacity to modulate attentional bias towards threatening information. Fifty healthy participants were randomly assigned to receive either anodal tDCS (2 mA/min) stimulation to the left dorsolateral prefrontal cortex (DLPFC), or sham. Participants were then eye tracked during a dual-video stressor task designed to elicit emotional reactivity, while providing a concurrent in-vivo measure of attentional bias. Greater attentional bias towards threatening information was associated with greater emotional reactivity to the stressor task. Furthermore, the active tDCS group showed reduced attentional bias to threat, compared to the sham group. Importantly, attentional bias was found to statistically mediate the effect of tDCS on emotional reactivity, while no direct effect of tDCS on emotional reactivity was observed. The findings are consistent with the notion that the effect of tDCS on emotional vulnerability may be mediated by changes in attentional bias, holding implications for the application of tDCS in emotion-based psychopathology. The findings also highlight the utility of in-vivo eye tracking measures in the examination of the mechanisms associated with DLPFC neuromodulation in emotional vulnerability. Copyright © 2017 Elsevier Ltd. All rights reserved.
QUANTIFYING THE BIASES OF SPECTROSCOPICALLY SELECTED GRAVITATIONAL LENSES
International Nuclear Information System (INIS)
Arneson, Ryan A.; Brownstein, Joel R.; Bolton, Adam S.
2012-01-01
Spectroscopic selection has been the most productive technique for the selection of galaxy-scale strong gravitational lens systems with known redshifts. Statistically significant samples of strong lenses provide a powerful method for measuring the mass-density parameters of the lensing population, but results can only be generalized to the parent population if the lensing selection biases are sufficiently understood. We perform controlled Monte Carlo simulations of spectroscopic lens surveys in order to quantify the bias of lenses relative to parent galaxies in velocity dispersion, mass axis ratio, and mass-density profile. For parameters typical of the SLACS and BELLS surveys, we find (1) no significant mass axis ratio detection bias of lenses relative to parent galaxies; (2) a very small detection bias toward shallow mass-density profiles, which is likely negligible compared to other sources of uncertainty in this parameter; (3) a detection bias toward smaller Einstein radius for systems drawn from parent populations with group- and cluster-scale lensing masses; and (4) a lens-modeling bias toward larger velocity dispersions for systems drawn from parent samples with sub-arcsecond mean Einstein radii. This last finding indicates that the incorporation of velocity-dispersion upper limits of non-lenses is an important ingredient for unbiased analyses of spectroscopically selected lens samples. In general, we find that the completeness of spectroscopic lens surveys in the plane of Einstein radius and mass-density profile power-law index is quite uniform, up to a sharp drop in the region of large Einstein radius and steep mass-density profile, and hence that such surveys are ideally suited to the study of massive field galaxies.
The threshold bias model: a mathematical model for the nomothetic approach of suicide.
Folly, Walter Sydney Dutra
2011-01-01
Comparative and predictive analyses of suicide data from different countries are difficult to perform due to varying approaches and the lack of comparative parameters. A simple model (the Threshold Bias Model) was tested for comparative and predictive analyses of suicide rates by age. The model comprises of a six parameter distribution that was applied to the USA suicide rates by age for the years 2001 and 2002. Posteriorly, linear extrapolations are performed of the parameter values previously obtained for these years in order to estimate the values corresponding to the year 2003. The calculated distributions agreed reasonably well with the aggregate data. The model was also used to determine the age above which suicide rates become statistically observable in USA, Brazil and Sri Lanka. The Threshold Bias Model has considerable potential applications in demographic studies of suicide. Moreover, since the model can be used to predict the evolution of suicide rates based on information extracted from past data, it will be of great interest to suicidologists and other researchers in the field of mental health.
A statistical mechanics approach to Granovetter theory
Barra, Adriano; Agliari, Elena
2012-05-01
In this paper we try to bridge breakthroughs in quantitative sociology/econometrics, pioneered during the last decades by Mac Fadden, Brock-Durlauf, Granovetter and Watts-Strogatz, by introducing a minimal model able to reproduce essentially all the features of social behavior highlighted by these authors. Our model relies on a pairwise Hamiltonian for decision-maker interactions which naturally extends the multi-populations approaches by shifting and biasing the pattern definitions of a Hopfield model of neural networks. Once introduced, the model is investigated through graph theory (to recover Granovetter and Watts-Strogatz results) and statistical mechanics (to recover Mac-Fadden and Brock-Durlauf results). Due to the internal symmetries of our model, the latter is obtained as the relaxation of a proper Markov process, allowing even to study its out-of-equilibrium properties. The method used to solve its equilibrium is an adaptation of the Hamilton-Jacobi technique recently introduced by Guerra in the spin-glass scenario and the picture obtained is the following: shifting the patterns from [-1,+1]→[0.+1] implies that the larger the amount of similarities among decision makers, the stronger their relative influence, and this is enough to explain both the different role of strong and weak ties in the social network as well as its small-world properties. As a result, imitative interaction strengths seem essentially a robust request (enough to break the gauge symmetry in the couplings), furthermore, this naturally leads to a discrete choice modelization when dealing with the external influences and to imitative behavior à la Curie-Weiss as the one introduced by Brock and Durlauf.
A Variational Approach to Simultaneous Image Segmentation and Bias Correction.
Zhang, Kaihua; Liu, Qingshan; Song, Huihui; Li, Xuelong
2015-08-01
This paper presents a novel variational approach for simultaneous estimation of bias field and segmentation of images with intensity inhomogeneity. We model intensity of inhomogeneous objects to be Gaussian distributed with different means and variances, and then introduce a sliding window to map the original image intensity onto another domain, where the intensity distribution of each object is still Gaussian but can be better separated. The means of the Gaussian distributions in the transformed domain can be adaptively estimated by multiplying the bias field with a piecewise constant signal within the sliding window. A maximum likelihood energy functional is then defined on each local region, which combines the bias field, the membership function of the object region, and the constant approximating the true signal from its corresponding object. The energy functional is then extended to the whole image domain by the Bayesian learning approach. An efficient iterative algorithm is proposed for energy minimization, via which the image segmentation and bias field correction are simultaneously achieved. Furthermore, the smoothness of the obtained optimal bias field is ensured by the normalized convolutions without extra cost. Experiments on real images demonstrated the superiority of the proposed algorithm to other state-of-the-art representative methods.
DEFF Research Database (Denmark)
Ramírez-Soriano, Anna; Nielsen, Rasmus
2009-01-01
Most single-nucleotide polymorphism (SNP) data suffer from an ascertainment bias caused by the process of SNP discovery followed by SNP genotyping. The final genotyped data are biased toward an excess of common alleles compared to directly sequenced data, making standard genetic methods of analysis...... the variances and covariances of these estimators and provide a corrected version of Tajima's D statistic. We reanalyze a human genomewide SNP data set and find substantial differences in the results with or without ascertainment bias correction....
An inclusive taxonomy of behavioral biases
Directory of Open Access Journals (Sweden)
David Peón
2017-07-01
Full Text Available This paper overviews the theoretical and empirical research on behavioral biases and their influence in the literature. To provide a systematic exposition, we present a unified framework that takes the reader through an original taxonomy, based on the reviews of relevant authors in the field. In particular, we establish three broad categories that may be distinguished: heuristics and biases; choices, values and frames; and social factors. We then describe the main biases within each category, and revise the main theoretical and empirical developments, linking each bias with other biases and anomalies that are related to them, according to the literature.
ASYMPTOTIC COMPARISONS OF U-STATISTICS, V-STATISTICS AND LIMITS OF BAYES ESTIMATES BY DEFICIENCIES
Toshifumi, Nomachi; Hajime, Yamato; Graduate School of Science and Engineering, Kagoshima University:Miyakonojo College of Technology; Faculty of Science, Kagoshima University
2001-01-01
As estimators of estimable parameters, we consider three statistics which are U-statistic, V-statistic and limit of Bayes estimate. This limit of Bayes estimate, called LB-statistic in this paper, is obtained from Bayes estimate of estimable parameter based on Dirichlet process, by letting its parameter tend to zero. For the estimable parameter with non-degenerate kernel, the asymptotic relative efficiencies of LB-statistic with respect to U-statistic and V-statistic and that of V-statistic w...
Coexisting exchange bias effect and ferroelectricity in geometrically frustrated ZnCr2O4
Dey, J. K.; Majumdar, S.; Giri, S.
2018-06-01
Concomitant occurrence of exchange bias effect and ferroelectric order is revealed in antiferromagnetic spinel ZnCr2O4. The exchange bias effect is observed below antiferromagnetic Neél temperature (T N) with a reasonable value of exchange bias field ( Oe at 2 K). Intriguingly, the ratio is found unusually high as ∼2.2, where H C is the coercivity. This indicates that large H C is not always primary for obtaining large exchange bias effect. Ferroelectric order is observed at T N, where non-centrosymmetric magnetic structure with space group associated with the magnetoelectric coupling correlates the ferroelectric order, proposing that, ZnCr2O4 is an improper multiferroic material. Rare occurrence of exchange bias effect and ferroelectric order in ZnCr2O4 attracts the community for fundamental interest and draws special attention in designing new materials for possible electric field control of exchange bias effect.
Quantifying selective reporting and the Proteus phenomenon for multiple datasets with similar bias.
Directory of Open Access Journals (Sweden)
Thomas Pfeiffer
2011-03-01
Full Text Available Meta-analyses play an important role in synthesizing evidence from diverse studies and datasets that address similar questions. A major obstacle for meta-analyses arises from biases in reporting. In particular, it is speculated that findings which do not achieve formal statistical significance are less likely reported than statistically significant findings. Moreover, the patterns of bias can be complex and may also depend on the timing of the research results and their relationship with previously published work. In this paper, we present an approach that is specifically designed to analyze large-scale datasets on published results. Such datasets are currently emerging in diverse research fields, particularly in molecular medicine. We use our approach to investigate a dataset on Alzheimer's disease (AD that covers 1167 results from case-control studies on 102 genetic markers. We observe that initial studies on a genetic marker tend to be substantially more biased than subsequent replications. The chances for initial, statistically non-significant results to be published are estimated to be about 44% (95% CI, 32% to 63% relative to statistically significant results, while statistically non-significant replications have almost the same chance to be published as statistically significant replications (84%; 95% CI, 66% to 107%. Early replications tend to be biased against initial findings, an observation previously termed Proteus phenomenon: The chances for non-significant studies going in the same direction as the initial result are estimated to be lower than the chances for non-significant studies opposing the initial result (73%; 95% CI, 55% to 96%. Such dynamic patterns in bias are difficult to capture by conventional methods, where typically simple publication bias is assumed to operate. Our approach captures and corrects for complex dynamic patterns of bias, and thereby helps generating conclusions from published results that are more robust
Savage, Leonard J
1972-01-01
Classic analysis of the foundations of statistics and development of personal probability, one of the greatest controversies in modern statistical thought. Revised edition. Calculus, probability, statistics, and Boolean algebra are recommended.
State Transportation Statistics 2010
2011-09-14
The Bureau of Transportation Statistics (BTS), a part of DOTs Research and Innovative Technology Administration (RITA), presents State Transportation Statistics 2010, a statistical profile of transportation in the 50 states and the District of Col...
State Transportation Statistics 2012
2013-08-15
The Bureau of Transportation Statistics (BTS), a part of the U.S. Department of Transportation's (USDOT) Research and Innovative Technology Administration (RITA), presents State Transportation Statistics 2012, a statistical profile of transportation ...
Adrenal Gland Tumors: Statistics
... Gland Tumor: Statistics Request Permissions Adrenal Gland Tumor: Statistics Approved by the Cancer.Net Editorial Board , 03/ ... primary adrenal gland tumor is very uncommon. Exact statistics are not available for this type of tumor ...
State transportation statistics 2009
2009-01-01
The Bureau of Transportation Statistics (BTS), a part of DOTs Research and : Innovative Technology Administration (RITA), presents State Transportation : Statistics 2009, a statistical profile of transportation in the 50 states and the : District ...
State Transportation Statistics 2011
2012-08-08
The Bureau of Transportation Statistics (BTS), a part of DOTs Research and Innovative Technology Administration (RITA), presents State Transportation Statistics 2011, a statistical profile of transportation in the 50 states and the District of Col...
Neuroendocrine Tumor: Statistics
... 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 ...
State Transportation Statistics 2013
2014-09-19
The Bureau of Transportation Statistics (BTS), a part of the U.S. Department of Transportations (USDOT) Research and Innovative Technology Administration (RITA), presents State Transportation Statistics 2013, a statistical profile of transportatio...
BTS statistical standards manual
2005-10-01
The Bureau of Transportation Statistics (BTS), like other federal statistical agencies, establishes professional standards to guide the methods and procedures for the collection, processing, storage, and presentation of statistical data. Standards an...
Gender Bias Affects Forests Worldwide
Directory of Open Access Journals (Sweden)
Marlène Elias
2017-04-01
Full Text Available Gender biases persist in forestry research and practice. These biases result in reduced scientific rigor and inequitable, ineffective, and less efficient policies, programs, and interventions. Drawing from a two-volume collection of current and classic analyses on gender in forests, we outline five persistent and inter-related themes: gendered governance, tree tenure, forest spaces, division of labor, and ecological knowledge. Each emerges across geographic regions in the northern and southern hemisphere and reflects inequities in women’s and men’s ability to make decisions about and benefit from trees, forests, and their products. Women’s ability to participate in community-based forest governance is typically less than men’s, causing concern for social equity and forest stewardship. Women’s access to trees and their products is commonly more limited than men’s, and mediated by their relationship with their male counterparts. Spatial patterns of forest use reflect gender norms and taboos, and men’s greater access to transportation. The division of labor results in gender specialization in the collection of forest products, with variations in gender roles across regions. All these gender differences result in ecological knowledge that is distinct but also complementary and shifting across the genders. The ways gender plays out in relation to each theme may vary across cultures and contexts, but the influence of gender, which intersects with other factors of social differentiation in shaping forest landscapes, is global.
Workplace ageism: discovering hidden bias.
Malinen, Sanna; Johnston, Lucy
2013-01-01
BACKGROUND/STUDY CONTEXT: Research largely shows no performance differences between older and younger employees, or that older workers even outperform younger employees, yet negative attitudes towards older workers can underpin discrimination. Unfortunately, traditional "explicit" techniques for assessing attitudes (i.e., self-report measures) have serious drawbacks. Therefore, using an approach that is novel to organizational contexts, the authors supplemented explicit with implicit (indirect) measures of attitudes towards older workers, and examined the malleability of both. This research consists of two studies. The authors measured self-report (explicit) attitudes towards older and younger workers with a survey, and implicit attitudes with a reaction-time-based measure of implicit associations. In addition, to test whether attitudes were malleable, the authors measured attitudes before and after a mental imagery intervention, where the authors asked participants in the experimental group to imagine respected and valued older workers from their surroundings. Negative, stable implicit attitudes towards older workers emerged in two studies. Conversely, explicit attitudes showed no age bias and were more susceptible to change intervention, such that attitudes became more positive towards older workers following the experimental manipulation. This research demonstrates the unconscious nature of bias against older workers, and highlights the utility of implicit attitude measures in the context of the workplace. In the current era of aging workforce and skill shortages, implicit measures may be necessary to illuminate hidden workplace ageism.
Statistical Discrimination in a Competitive Labor Market
Jonathan B. Berk
1999-01-01
This paper studies the effect of employee job selection in a model of statistical discrimination in a competitive labor market. In an economy in which there are quality differences between groups, a surprisingly strong condition is required to guarantee discrimination against the worse qualified group --- MLRP must hold. In addition, because of the self-selection bias induced by competition, the resulting discrimination is small when compared to the magnitude of the underlying quality differe...
Analysis of statistical misconception in terms of statistical reasoning
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.
Kim, E.; Newton, A. P.
2012-04-01
One major problem in dynamo theory is the multi-scale nature of the MHD turbulence, which requires statistical theory in terms of probability distribution functions. In this contribution, we present the statistical theory of magnetic fields in a simplified mean field α-Ω dynamo model by varying the statistical property of alpha, including marginal stability and intermittency, and then utilize observational data of solar activity to fine-tune the mean field dynamo model. Specifically, we first present a comprehensive investigation into the effect of the stochastic parameters in a simplified α-Ω dynamo model. Through considering the manifold of marginal stability (the region of parameter space where the mean growth rate is zero), we show that stochastic fluctuations are conductive to dynamo. Furthermore, by considering the cases of fluctuating alpha that are periodic and Gaussian coloured random noise with identical characteristic time-scales and fluctuating amplitudes, we show that the transition to dynamo is significantly facilitated for stochastic alpha with random noise. Furthermore, we show that probability density functions (PDFs) of the growth-rate, magnetic field and magnetic energy can provide a wealth of useful information regarding the dynamo behaviour/intermittency. Finally, the precise statistical property of the dynamo such as temporal correlation and fluctuating amplitude is found to be dependent on the distribution the fluctuations of stochastic parameters. We then use observations of solar activity to constrain parameters relating to the effect in stochastic α-Ω nonlinear dynamo models. This is achieved through performing a comprehensive statistical comparison by computing PDFs of solar activity from observations and from our simulation of mean field dynamo model. The observational data that are used are the time history of solar activity inferred for C14 data in the past 11000 years on a long time scale and direct observations of the sun spot
Potential Reporting Bias in Neuroimaging Studies of Sex Differences.
David, Sean P; Naudet, Florian; Laude, Jennifer; Radua, Joaquim; Fusar-Poli, Paolo; Chu, Isabella; Stefanick, Marcia L; Ioannidis, John P A
2018-04-17
Numerous functional magnetic resonance imaging (fMRI) studies have reported sex differences. To empirically evaluate for evidence of excessive significance bias in this literature, we searched for published fMRI studies of human brain to evaluate sex differences, regardless of the topic investigated, in Medline and Scopus over 10 years. We analyzed the prevalence of conclusions in favor of sex differences and the correlation between study sample sizes and number of significant foci identified. In the absence of bias, larger studies (better powered) should identify a larger number of significant foci. Across 179 papers, median sample size was n = 32 (interquartile range 23-47.5). A median of 5 foci related to sex differences were reported (interquartile range, 2-9.5). Few articles (n = 2) had titles focused on no differences or on similarities (n = 3) between sexes. Overall, 158 papers (88%) reached "positive" conclusions in their abstract and presented some foci related to sex differences. There was no statistically significant relationship between sample size and the number of foci (-0.048% increase for every 10 participants, p = 0.63). The extremely high prevalence of "positive" results and the lack of the expected relationship between sample size and the number of discovered foci reflect probable reporting bias and excess significance bias in this literature.
HMO marketing and selection bias: are TEFRA HMOs skimming?
Lichtenstein, R; Thomas, J W; Watkins, B; Puto, C; Lepkowski, J; Adams-Watson, J; Simone, B; Vest, D
1992-04-01
The research evidence indicates that health maintenance organizations (HMOs) participating in the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) At-Risk Program tend to experience favorable selection. Although favorable selection might result from patient decisions, a common conjecture is that it can be induced by HMOs through their marketing activities. The purpose of this study is to examine the relationship between HMO marketing strategies and selection bias in TEFRA At-Risk HMOs. A purposive sample of 22 HMOs that were actively marketing their TEFRA programs was selected and data on organizational characteristics, market area characteristics, and HMO marketing decisions were collected. To measure selection bias in these HMOs, the functional health status of approximately 300 enrollees in each HMO was compared to that of 300 non-enrolling beneficiaries in the same area. Three dependent variables, reflecting selection bias at the mean, the low health tail, and the high health tail of the health status distribution were created. Weighted least squares regressions were then used to identify relationships between marketing elements and selection bias. Subject to the statistical limitations of the study, our conclusion is that it is doubtful that HMO marketing decisions are responsible for the prevalence of favorable selection in HMO enrollment. It also appears unlikely that HMOs were differentially targeting healthy and unhealthy segments of the Medicare market.
Analysis of the theoretical bias in dark matter direct detection
International Nuclear Information System (INIS)
Catena, Riccardo
2014-01-01
Fitting the model ''A'' to dark matter direct detection data, when the model that underlies the data is ''B'', introduces a theoretical bias in the fit. We perform a quantitative study of the theoretical bias in dark matter direct detection, with a focus on assumptions regarding the dark matter interactions, and velocity distribution. We address this problem within the effective theory of isoscalar dark matter-nucleon interactions mediated by a heavy spin-1 or spin-0 particle. We analyze 24 benchmark points in the parameter space of the theory, using frequentist and Bayesian statistical methods. First, we simulate the data of future direct detection experiments assuming a momentum/velocity dependent dark matter-nucleon interaction, and an anisotropic dark matter velocity distribution. Then, we fit a constant scattering cross section, and an isotropic Maxwell-Boltzmann velocity distribution to the simulated data, thereby introducing a bias in the analysis. The best fit values of the dark matter particle mass differ from their benchmark values up to 2 standard deviations. The best fit values of the dark matter-nucleon coupling constant differ from their benchmark values up to several standard deviations. We conclude that common assumptions in dark matter direct detection are a source of potentially significant bias
Operator Bias in the Estimation of Arc Efficiency in Gas Tungsten Arc Welding
Directory of Open Access Journals (Sweden)
Fredrik Sikström
2015-03-01
Full Text Available In this paper the operator bias in the measurement process of arc efficiency in stationary direct current electrode negative gas tungsten arc welding is discussed. An experimental study involving 15 operators (enough to reach statistical significance has been carried out with the purpose to estimate the arc efficiency from a specific procedure for calorimetric experiments. The measurement procedure consists of three manual operations which introduces operator bias in the measurement process. An additional relevant experiment highlights the consequences of estimating the arc voltage by measuring the potential between the terminals of the welding power source instead of measuring the potential between the electrode contact tube and the workpiece. The result of the study is a statistical evaluation of the operator bias influence on the estimate, showing that operator bias is negligible in the estimate considered here. On the contrary the consequences of neglecting welding leads voltage drop results in a significant under estimation of the arc efficiency.
Isotopic safeguards statistics
International Nuclear Information System (INIS)
Timmerman, C.L.; Stewart, K.B.
1978-06-01
The methods and results of our statistical analysis of isotopic data using isotopic safeguards techniques are illustrated using example data from the Yankee Rowe reactor. The statistical methods used in this analysis are the paired comparison and the regression analyses. A paired comparison results when a sample from a batch is analyzed by two different laboratories. Paired comparison techniques can be used with regression analysis to detect and identify outlier batches. The second analysis tool, linear regression, involves comparing various regression approaches. These approaches use two basic types of models: the intercept model (y = α + βx) and the initial point model [y - y 0 = β(x - x 0 )]. The intercept model fits strictly the exposure or burnup values of isotopic functions, while the initial point model utilizes the exposure values plus the initial or fabricator's data values in the regression analysis. Two fitting methods are applied to each of these models. These methods are: (1) the usual least squares fitting approach where x is measured without error, and (2) Deming's approach which uses the variance estimates obtained from the paired comparison results and considers x and y are both measured with error. The Yankee Rowe data were first measured by Nuclear Fuel Services (NFS) and remeasured by Nuclear Audit and Testing Company (NATCO). The ratio of Pu/U versus 235 D (in which 235 D is the amount of depleted 235 U expressed in weight percent) using actual numbers is the isotopic function illustrated. Statistical results using the Yankee Rowe data indicates the attractiveness of Deming's regression model over the usual approach by simple comparison of the given regression variances with the random variance from the paired comparison results
Significance of Bias Correction in Drought Frequency and Scenario Analysis Based on Climate Models
Aryal, Y.; Zhu, J.
2015-12-01
Assessment of future drought characteristics is difficult as climate models usually have bias in simulating precipitation frequency and intensity. To overcome this limitation, output from climate models need to be bias corrected based on the specific purpose of applications. In this study, we examine the significance of bias correction in the context of drought frequency and scenario analysis using output from climate models. In particular, we investigate the performance of three widely used bias correction techniques: (1) monthly bias correction (MBC), (2) nested bias correction (NBC), and (3) equidistance quantile mapping (EQM) The effect of bias correction in future scenario of drought frequency is also analyzed. The characteristics of drought are investigated in terms of frequency and severity in nine representative locations in different climatic regions across the United States using regional climate model (RCM) output from the North American Regional Climate Change Assessment Program (NARCCAP). The Standardized Precipitation Index (SPI) is used as the means to compare and forecast drought characteristics at different timescales. Systematic biases in the RCM precipitation output are corrected against the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) data. The results demonstrate that bias correction significantly decreases the RCM errors in reproducing drought frequency derived from the NARR data. Preserving mean and standard deviation is essential for climate models in drought frequency analysis. RCM biases both have regional and timescale dependence. Different timescale of input precipitation in the bias corrections show similar results. Drought frequency obtained from the RCM future (2040-2070) scenarios is compared with that from the historical simulations. The changes in drought characteristics occur in all climatic regions. The relative changes in drought frequency in future scenario in relation to
Ensemble stacking mitigates biases in inference of synaptic connectivity.
Chambers, Brendan; Levy, Maayan; Dechery, Joseph B; MacLean, Jason N
2018-01-01
A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches.
An importance biasing for 1-D deep-penetration problem by Monte Carlo
International Nuclear Information System (INIS)
Gupta, H.C.; Dwivedi, S.R.
1988-01-01
Using the itegral equations for the first and second moments of the 'total score' in an analogue and non-analogue simulations zero-variance biasing schemes have been obtained for all the commonly used reaction rate estimators. For partial score estimators a new zero-variance biasing scheme has been obtained as a special case. The new zero-variance scheme developed for partial score estimators has been used to develop an importance biasing scheme for use with expectation estimator in one dimensional deep-penetration problems with isotropic scattering. The importance biasing scheme has been studied for variance reduction in shields with anisotropic scattering. It is observed that the scheme not only results into a significant reduction in variance over the exponential biasing but also simplifies the complicated sampling procedure for the particle's outgoing direction at collision point. (author). 27 tables, 79 refs
Experimental results obtained at GANIL
International Nuclear Information System (INIS)
Borrel, V.
1993-01-01
A review of experimental results obtained at GANIL on the study of nuclear structure and nuclear reactions with secondary radioactive beams is presented. Mass measurements by means of the GANIL cyclotrons are described. The possibilities of GANIL/LISE3 for the production and separation of radioactive beams are illustrated through a large variety of experiments. (author). 19 refs., 8 figs
Reporting bias in medical research - a narrative review
Directory of Open Access Journals (Sweden)
Kölsch Heike
2010-04-01
Full Text Available Abstract Reporting bias represents a major problem in the assessment of health care interventions. Several prominent cases have been described in the literature, for example, in the reporting of trials of antidepressants, Class I anti-arrhythmic drugs, and selective COX-2 inhibitors. The aim of this narrative review is to gain an overview of reporting bias in the medical literature, focussing on publication bias and selective outcome reporting. We explore whether these types of bias have been shown in areas beyond the well-known cases noted above, in order to gain an impression of how widespread the problem is. For this purpose, we screened relevant articles on reporting bias that had previously been obtained by the German Institute for Quality and Efficiency in Health Care in the context of its health technology assessment reports and other research work, together with the reference lists of these articles. We identified reporting bias in 40 indications comprising around 50 different pharmacological, surgical (e.g. vacuum-assisted closure therapy, diagnostic (e.g. ultrasound, and preventive (e.g. cancer vaccines interventions. Regarding pharmacological interventions, cases of reporting bias were, for example, identified in the treatment of the following conditions: depression, bipolar disorder, schizophrenia, anxiety disorder, attention-deficit hyperactivity disorder, Alzheimer's disease, pain, migraine, cardiovascular disease, gastric ulcers, irritable bowel syndrome, urinary incontinence, atopic dermatitis, diabetes mellitus type 2, hypercholesterolaemia, thyroid disorders, menopausal symptoms, various types of cancer (e.g. ovarian cancer and melanoma, various types of infections (e.g. HIV, influenza and Hepatitis B, and acute trauma. Many cases involved the withholding of study data by manufacturers and regulatory agencies or the active attempt by manufacturers to suppress publication. The ascertained effects of reporting bias included the
Quantum-statistical kinetic equations
International Nuclear Information System (INIS)
Loss, D.; Schoeller, H.
1989-01-01
Considering a homogeneous normal quantum fluid consisting of identical interacting fermions or bosons, the authors derive an exact quantum-statistical generalized kinetic equation with a collision operator given as explicit cluster series where exchange effects are included through renormalized Liouville operators. This new result is obtained by applying a recently developed superoperator formalism (Liouville operators, cluster expansions, symmetrized projectors, P q -rule, etc.) to nonequilibrium systems described by a density operator ρ(t) which obeys the von Neumann equation. By means of this formalism a factorization theorem is proven (being essential for obtaining closed equations), and partial resummations (leading to renormalized quantities) are performed. As an illustrative application, the quantum-statistical versions (including exchange effects due to Fermi-Dirac or Bose-Einstein statistics) of the homogeneous Boltzmann (binary collisions) and Choh-Uhlenbeck (triple collisions) equations are derived
Order, disorder and generalized statistics
International Nuclear Information System (INIS)
Marino, E.C.; Swieca, J.A.
1980-06-01
We generalize the prescription of Kadanoff and Ceva for the computation of disorder variables correlation functions in the Ising model for continuous field theories with U(1) symmetry. By considering the product of order and disorder variables, we obtain a path integral representation for fields with generalized statistics. We discuss in detail the cases of massless Thirring and Schwinger models. (Author) [pt
Order, disorder and generalized statistics
International Nuclear Information System (INIS)
Marino, E.C.; Swieca, J.A.; Pontificia Universidade Catolica do Rio de Janeiro
1980-01-01
We generalize the prescription of Kadanoff and Ceva for the computation of disorder variable correlation functions in the Ising model for continuous field theories with U(1) symmetry. By considering the product of order and disorder variables, we obtain a path integral representation for fields with generalized statistics. We discuss in detail the cases of massless Thirring and Schwinger models. (orig.)
Classical model of intermediate statistics
International Nuclear Information System (INIS)
Kaniadakis, G.
1994-01-01
In this work we present a classical kinetic model of intermediate statistics. In the case of Brownian particles we show that the Fermi-Dirac (FD) and Bose-Einstein (BE) distributions can be obtained, just as the Maxwell-Boltzmann (MD) distribution, as steady states of a classical kinetic equation that intrinsically takes into account an exclusion-inclusion principle. In our model the intermediate statistics are obtained as steady states of a system of coupled nonlinear kinetic equations, where the coupling constants are the transmutational potentials η κκ' . We show that, besides the FD-BE intermediate statistics extensively studied from the quantum point of view, we can also study the MB-FD and MB-BE ones. Moreover, our model allows us to treat the three-state mixing FD-MB-BE intermediate statistics. For boson and fermion mixing in a D-dimensional space, we obtain a family of FD-BE intermediate statistics by varying the transmutational potential η BF . This family contains, as a particular case when η BF =0, the quantum statistics recently proposed by L. Wu, Z. Wu, and J. Sun [Phys. Lett. A 170, 280 (1992)]. When we consider the two-dimensional FD-BE statistics, we derive an analytic expression of the fraction of fermions. When the temperature T→∞, the system is composed by an equal number of bosons and fermions, regardless of the value of η BF . On the contrary, when T=0, η BF becomes important and, according to its value, the system can be completely bosonic or fermionic, or composed both by bosons and fermions
Domain-size-dependent exchange bias in Co/LaFeO3
Energy Technology Data Exchange (ETDEWEB)
Scholl, A.; Nolting, F.; Seo, J.W.; Ohldag, H.; Stohr, J.; Raoux,S.; Locquet, J.-P.; Fompeyrine, J.
2004-09-22
X-ray microscopy using magnetic linear dichroism of a zero-field-grown, multi-domain Co/LaFeO{sub 3} ferromagnet/antiferromagnet sample shows a local exchange bias of random direction and magnitude. A statistical analysis of the local bias of individual, micron-size magnetic domains demonstrates an increasing bias field with decreasing domain size as expected for a random distribution of pinned, uncompensated spins, which are believed to mediate the interface coupling. A linear dependence with the inverse domain diameter is found.
Social reward shapes attentional biases.
Anderson, Brian A
2016-01-01
Paying attention to stimuli that predict a reward outcome is important for an organism to survive and thrive. When visual stimuli are associated with tangible, extrinsic rewards such as money or food, these stimuli acquire high attentional priority and come to automatically capture attention. In humans and other primates, however, many behaviors are not motivated directly by such extrinsic rewards, but rather by the social feedback that results from performing those behaviors. In the present study, I examine whether positive social feedback can similarly influence attentional bias. The results show that stimuli previously associated with a high probability of positive social feedback elicit value-driven attentional capture, much like stimuli associated with extrinsic rewards. Unlike with extrinsic rewards, however, such stimuli also influence task-specific motivation. My findings offer a potential mechanism by which social reward shapes the information that we prioritize when perceiving the world around us.
Ratio Bias and Policy Preferences
DEFF Research Database (Denmark)
Pedersen, Rasmus Tue
2017-01-01
Numbers permeate modern political communication. While current scholarship on framing effects has focused on the persuasive effects of words and arguments, this article shows that framing of numbers can also substantially affect policy preferences. Such effects are caused by ratio bias, which...... is a general tendency to focus on numerators and pay insufficient attention to denominators in ratios. Using a population-based survey experiment, I demonstrate how differently framed but logically equivalent representations of the exact same numerical value can have large effects on citizens’ preferences...... regarding salient political issues such as education and taxes. Furthermore, the effects of numerical framing are found across most groups of the population, largely regardless of their political predisposition and their general ability to understand and use numerical information. These findings have...
Dynamic statistical information theory
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
In recent years we extended Shannon static statistical information theory to dynamic processes and established a Shannon dynamic statistical information theory, whose core is the evolution law of dynamic entropy and dynamic information. We also proposed a corresponding Boltzmman dynamic statistical information theory. Based on the fact that the state variable evolution equation of respective dynamic systems, i.e. Fokker-Planck equation and Liouville diffusion equation can be regarded as their information symbol evolution equation, we derived the nonlinear evolution equations of Shannon dynamic entropy density and dynamic information density and the nonlinear evolution equations of Boltzmann dynamic entropy density and dynamic information density, that describe respectively the evolution law of dynamic entropy and dynamic information. The evolution equations of these two kinds of dynamic entropies and dynamic informations show in unison that the time rate of change of dynamic entropy densities is caused by their drift, diffusion and production in state variable space inside the systems and coordinate space in the transmission processes; and that the time rate of change of dynamic information densities originates from their drift, diffusion and dissipation in state variable space inside the systems and coordinate space in the transmission processes. Entropy and information have been combined with the state and its law of motion of the systems. Furthermore we presented the formulas of two kinds of entropy production rates and information dissipation rates, the expressions of two kinds of drift information flows and diffusion information flows. We proved that two kinds of information dissipation rates (or the decrease rates of the total information) were equal to their corresponding entropy production rates (or the increase rates of the total entropy) in the same dynamic system. We obtained the formulas of two kinds of dynamic mutual informations and dynamic channel
Ringard, Justine; Seyler, Frederique; Linguet, Laurent
2017-06-16
Satellite precipitation products (SPPs) provide alternative precipitation data for regions with sparse rain gauge measurements. However, SPPs are subject to different types of error that need correction. Most SPP bias correction methods use the statistical properties of the rain gauge data to adjust the corresponding SPP data. The statistical adjustment does not make it possible to correct the pixels of SPP data for which there is no rain gauge data. The solution proposed in this article is to correct the daily SPP data for the Guiana Shield using a novel two set approach, without taking into account the daily gauge data of the pixel to be corrected, but the daily gauge data from surrounding pixels. In this case, a spatial analysis must be involved. The first step defines hydroclimatic areas using a spatial classification that considers precipitation data with the same temporal distributions. The second step uses the Quantile Mapping bias correction method to correct the daily SPP data contained within each hydroclimatic area. We validate the results by comparing the corrected SPP data and daily rain gauge measurements using relative RMSE and relative bias statistical errors. The results show that analysis scale variation reduces rBIAS and rRMSE significantly. The spatial classification avoids mixing rainfall data with different temporal characteristics in each hydroclimatic area, and the defined bias correction parameters are more realistic and appropriate. This study demonstrates that hydroclimatic classification is relevant for implementing bias correction methods at the local scale.
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Culture Moderates Biases in Search Decisions.
Pattaratanakun, Jake A; Mak, Vincent
2015-08-01
Prior studies suggest that people often search insufficiently in sequential-search tasks compared with the predictions of benchmark optimal strategies that maximize expected payoff. However, those studies were mostly conducted in individualist Western cultures; Easterners from collectivist cultures, with their higher susceptibility to escalation of commitment induced by sunk search costs, could exhibit a reversal of this undersearch bias by searching more than optimally, but only when search costs are high. We tested our theory in four experiments. In our pilot experiment, participants generally undersearched when search cost was low, but only Eastern participants oversearched when search cost was high. In Experiments 1 and 2, we obtained evidence for our hypothesized effects via a cultural-priming manipulation on bicultural participants in which we manipulated the language used in the program interface. We obtained further process evidence for our theory in Experiment 3, in which we made sunk costs nonsalient in the search task-as expected, cross-cultural effects were largely mitigated. © The Author(s) 2015.
Geopolymer obtained from coal ash
International Nuclear Information System (INIS)
Conte, V.; Bissari, E.S.; Uggioni, E.; Bernardin, A.M.
2011-01-01
Geopolymers are three-dimensional alumino silicates that can be rapidly formed at low temperature from naturally occurring aluminosilicates with a structure similar to zeolites. In this work coal ash (Tractebel Energy) was used as source of aluminosilicate according a full factorial design in eight formulations with three factors (hydroxide type and concentration and temperature) and two-levels. The ash was dried and hydroxide was added according type and concentration. The geopolymer was poured into cylindrical molds, cured (14 days) and subjected to compression test. The coal ash from power plants belongs to the Si-Al system and thus can easily form geopolymers. The compression tests showed that it is possible to obtain samples with strength comparable to conventional Portland cement. As a result, temperature and molarity are the main factors affecting the compressive strength of the obtained geopolymer. (author)
Good practices for quantitative bias analysis.
Lash, Timothy L; Fox, Matthew P; MacLehose, Richard F; Maldonado, George; McCandless, Lawrence C; Greenland, Sander
2014-12-01
Quantitative bias analysis serves several objectives in epidemiological research. First, it provides a quantitative estimate of the direction, magnitude and uncertainty arising from systematic errors. Second, the acts of identifying sources of systematic error, writing down models to quantify them, assigning values to the bias parameters and interpreting the results combat the human tendency towards overconfidence in research results, syntheses and critiques and the inferences that rest upon them. Finally, by suggesting aspects that dominate uncertainty in a particular research result or topic area, bias analysis can guide efficient allocation of sparse research resources. The fundamental methods of bias analyses have been known for decades, and there have been calls for more widespread use for nearly as long. There was a time when some believed that bias analyses were rarely undertaken because the methods were not widely known and because automated computing tools were not readily available to implement the methods. These shortcomings have been largely resolved. We must, therefore, contemplate other barriers to implementation. One possibility is that practitioners avoid the analyses because they lack confidence in the practice of bias analysis. The purpose of this paper is therefore to describe what we view as good practices for applying quantitative bias analysis to epidemiological data, directed towards those familiar with the methods. We focus on answering questions often posed to those of us who advocate incorporation of bias analysis methods into teaching and research. These include the following. When is bias analysis practical and productive? How does one select the biases that ought to be addressed? How does one select a method to model biases? How does one assign values to the parameters of a bias model? How does one present and interpret a bias analysis?. We hope that our guide to good practices for conducting and presenting bias analyses will encourage
The Bias in Bayes and How to Measure it
Directory of Open Access Journals (Sweden)
D.A. S. Fraser
2012-07-01
Full Text Available A Bayes prior with a likelihood can give approximate confidence and provide a remarkably flexible approach to statistical inference; but is also known to provide inaccurate perhaps incorrect results. We develop a measure of Bayes bias, first examining a simple Normal model and then progressing to quite general models with scalar and vector parameters. The Bias measure can be interpreted as the lateral displacement of the location standardized likelihood function and thus provides ready access to the effect of a prior on p-values, confidence bounds, and Bayes posterior bounds. The needed computation is comparable to that for the likelihood function and thus provides an initial option for checking merits of Bayesian computation for high dimensions.
Cognitive advantage in bilingualism: an example of publication bias?
de Bruin, Angela; Treccani, Barbara; Della Sala, Sergio
2015-01-01
It is a widely held belief that bilinguals have an advantage over monolinguals in executive-control tasks, but is this what all studies actually demonstrate? The idea of a bilingual advantage may result from a publication bias favoring studies with positive results over studies with null or negative effects. To test this hypothesis, we looked at conference abstracts from 1999 to 2012 on the topic of bilingualism and executive control. We then determined which of the studies they reported were subsequently published. Studies with results fully supporting the bilingual-advantage theory were most likely to be published, followed by studies with mixed results. Studies challenging the bilingual advantage were published the least. This discrepancy was not due to differences in sample size, tests used, or statistical power. A test for funnel-plot asymmetry provided further evidence for the existence of a publication bias. © The Author(s) 2014.
Emissive limiter bias experiment for improved confinement of tokamaks
International Nuclear Information System (INIS)
Choe, W.; Ono, M.; Darrow, D.S.; Pribyl, P.A.; Liberati, J.R.; Taylor, R.J.
1992-01-01
Experiments have been performed in Ohmic discharges of the UCLA CCT tokamak with a LaB 6 biased limiter, capable of emitting energetic electrons as a technique to improve confinement in tokamaks. To study the effects of emitted electrons, the limiter position, bias voltage, and plasma position were varied. The results have shown that the plasma positioning with respect to the emissive limiter plays an important role in obtaining H-mode plasmas. The emissive cathode must be located close to the last closed flux surface in order to charge up the plasma. As the cathode is moved closer to the wall, the positioning of the plasma becomes more critical since the plasma can easily detach from the cathode and reattach to the wall, resulting in the termination of H-mode. The emissive capability appears to be important for operating at lower bias voltage and reducing impurity levels in the plasma. With a heated cathode, transition to H-mode was observed for V bias ≤ 50 V and I inj ≥ 30 A. At a lower cathode heater current, a higher bias voltage is required for the transition. Moreover, with a lower cathode heater current, the time delay for inducing H-mode becomes longer, which can be attributed to the required time for the self-heating of the cathode to reach the emissive temperature. From this result, we conclude that the capacity for emission can significantly improve the performance of limiter biasing for inducing H-mode transition. With L-mode plasmas, the injection current flowing out of the cathode was generally higher than 100 A
Estimates of bias and uncertainty in recorded external dose
International Nuclear Information System (INIS)
Fix, J.J.; Gilbert, E.S.; Baumgartner, W.V.
1994-10-01
A study is underway to develop an approach to quantify bias and uncertainty in recorded dose estimates for workers at the Hanford Site based on personnel dosimeter results. This paper focuses on selected experimental studies conducted to better define response characteristics of Hanford dosimeters. The study is more extensive than the experimental studies presented in this paper and includes detailed consideration and evaluation of other sources of bias and uncertainty. Hanford worker dose estimates are used in epidemiologic studies of nuclear workers. A major objective of these studies is to provide a direct assessment of the carcinogenic risk of exposure to ionizing radiation at low doses and dose rates. Considerations of bias and uncertainty in the recorded dose estimates are important in the conduct of this work. The method developed for use with Hanford workers can be considered an elaboration of the approach used to quantify bias and uncertainty in estimated doses for personnel exposed to radiation as a result of atmospheric testing of nuclear weapons between 1945 and 1962. This approach was first developed by a National Research Council (NRC) committee examining uncertainty in recorded film badge doses during atmospheric tests (NRC 1989). It involved quantifying both bias and uncertainty from three sources (i.e., laboratory, radiological, and environmental) and then combining them to obtain an overall assessment. Sources of uncertainty have been evaluated for each of three specific Hanford dosimetry systems (i.e., the Hanford two-element film dosimeter, 1944-1956; the Hanford multi-element film dosimeter, 1957-1971; and the Hanford multi-element TLD, 1972-1993) used to estimate personnel dose throughout the history of Hanford operations. Laboratory, radiological, and environmental sources of bias and uncertainty have been estimated based on historical documentation and, for angular response, on selected laboratory measurements
Tangborn, Andrew; Menard, Richard; Ortland, David; Einaudi, Franco (Technical Monitor)
2001-01-01
A new approach to the analysis of systematic and random observation errors is presented in which the error statistics are obtained using forecast data rather than observations from a different instrument type. The analysis is carried out at an intermediate retrieval level, instead of the more typical state variable space. This method is carried out on measurements made by the High Resolution Doppler Imager (HRDI) on board the Upper Atmosphere Research Satellite (UARS). HRDI, a limb sounder, is the only satellite instrument measuring winds in the stratosphere, and the only instrument of any kind making global wind measurements in the upper atmosphere. HRDI measures doppler shifts in the two different O2 absorption bands (alpha and B) and the retrieved products are tangent point Line-of-Sight wind component (level 2 retrieval) and UV winds (level 3 retrieval). This analysis is carried out on a level 1.9 retrieval, in which the contributions from different points along the line-of-sight have not been removed. Biases are calculated from O-F (observed minus forecast) LOS wind components and are separated into a measurement parameter space consisting of 16 different values. The bias dependence on these parameters (plus an altitude dependence) is used to create a bias correction scheme carried out on the level 1.9 retrieval. The random error component is analyzed by separating the gamma and B band observations and locating observation pairs where both bands are very nearly looking at the same location at the same time. It is shown that the two observation streams are uncorrelated and that this allows the forecast error variance to be estimated. The bias correction is found to cut the effective observation error variance in half.
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
Probing Biased Signaling in Chemokine Receptors
DEFF Research Database (Denmark)
Amarandi, Roxana Maria; Hjortø, Gertrud Malene; Rosenkilde, Mette Marie
2016-01-01
The chemokine system mediates leukocyte migration during homeostatic and inflammatory processes. Traditionally, it is described as redundant and promiscuous, with a single chemokine ligand binding to different receptors and a single receptor having several ligands. Signaling of chemokine receptors...... of others has been termed signaling bias and can accordingly be grouped into ligand bias, receptor bias, and tissue bias. Bias has so far been broadly overlooked in the process of drug development. The low number of currently approved drugs targeting the chemokine system, as well as the broad range...... of failed clinical trials, reflects the need for a better understanding of the chemokine system. Thus, understanding the character, direction, and consequence of biased signaling in the chemokine system may aid the development of new therapeutics. This review describes experiments to assess G protein...
Symmetry as Bias: Rediscovering Special Relativity
Lowry, Michael R.
1992-01-01
This paper describes a rational reconstruction of Einstein's discovery of special relativity, validated through an implementation: the Erlanger program. Einstein's discovery of special relativity revolutionized both the content of physics and the research strategy used by theoretical physicists. This research strategy entails a mutual bootstrapping process between a hypothesis space for biases, defined through different postulated symmetries of the universe, and a hypothesis space for physical theories. The invariance principle mutually constrains these two spaces. The invariance principle enables detecting when an evolving physical theory becomes inconsistent with its bias, and also when the biases for theories describing different phenomena are inconsistent. Structural properties of the invariance principle facilitate generating a new bias when an inconsistency is detected. After a new bias is generated. this principle facilitates reformulating the old, inconsistent theory by treating the latter as a limiting approximation. The structural properties of the invariance principle can be suitably generalized to other types of biases to enable primal-dual learning.
Bias detection and certified reference materials for random measurands
Rukhin, Andrew L.
2015-12-01
A problem that frequently occurs in metrology is the bias checking of data obtained by a laboratory against the specified value and uncertainty estimate given in the certificate of analysis. The measurand—a property of a certified reference material (CRM)—is supposed to be random with a normal distribution whose parameters are given by the certificate specifications. The laboratory’s data from subsequent measurements of the CRM (a CRM experiment) are summarized by the sample mean value and its uncertainty which is commonly based on a repeatability standard deviation. New confidence intervals for the lab’s bias are derived. Although they may lack intuitive appeal, those obtained by using higher order asymptotic methods, compared and contrasted in this paper, are recommended.
Long-branch attraction bias and inconsistency in Bayesian phylogenetics.
Kolaczkowski, Bryan; Thornton, Joseph W
2009-12-09
Bayesian inference (BI) of phylogenetic relationships uses the same probabilistic models of evolution as its precursor maximum likelihood (ML), so BI has generally been assumed to share ML's desirable statistical properties, such as largely unbiased inference of topology given an accurate model and increasingly reliable inferences as the amount of data increases. Here we show that BI, unlike ML, is biased in favor of topologies that group long branches together, even when the true model and prior distributions of evolutionary parameters over a group of phylogenies are known. Using experimental simulation studies and numerical and mathematical analyses, we show that this bias becomes more severe as more data are analyzed, causing BI to infer an incorrect tree as the maximum a posteriori phylogeny with asymptotically high support as sequence length approaches infinity. BI's long branch attraction bias is relatively weak when the true model is simple but becomes pronounced when sequence sites evolve heterogeneously, even when this complexity is incorporated in the model. This bias--which is apparent under both controlled simulation conditions and in analyses of empirical sequence data--also makes BI less efficient and less robust to the use of an incorrect evolutionary model than ML. Surprisingly, BI's bias is caused by one of the method's stated advantages--that it incorporates uncertainty about branch lengths by integrating over a distribution of possible values instead of estimating them from the data, as ML does. Our findings suggest that trees inferred using BI should be interpreted with caution and that ML may be a more reliable framework for modern phylogenetic analysis.
Long-branch attraction bias and inconsistency in Bayesian phylogenetics.
Directory of Open Access Journals (Sweden)
Bryan Kolaczkowski
Full Text Available Bayesian inference (BI of phylogenetic relationships uses the same probabilistic models of evolution as its precursor maximum likelihood (ML, so BI has generally been assumed to share ML's desirable statistical properties, such as largely unbiased inference of topology given an accurate model and increasingly reliable inferences as the amount of data increases. Here we show that BI, unlike ML, is biased in favor of topologies that group long branches together, even when the true model and prior distributions of evolutionary parameters over a group of phylogenies are known. Using experimental simulation studies and numerical and mathematical analyses, we show that this bias becomes more severe as more data are analyzed, causing BI to infer an incorrect tree as the maximum a posteriori phylogeny with asymptotically high support as sequence length approaches infinity. BI's long branch attraction bias is relatively weak when the true model is simple but becomes pronounced when sequence sites evolve heterogeneously, even when this complexity is incorporated in the model. This bias--which is apparent under both controlled simulation conditions and in analyses of empirical sequence data--also makes BI less efficient and less robust to the use of an incorrect evolutionary model than ML. Surprisingly, BI's bias is caused by one of the method's stated advantages--that it incorporates uncertainty about branch lengths by integrating over a distribution of possible values instead of estimating them from the data, as ML does. Our findings suggest that trees inferred using BI should be interpreted with caution and that ML may be a more reliable framework for modern phylogenetic analysis.
Hebert, J R; Clemow, L; Pbert, L; Ockene, I S; Ockene, J K
1995-04-01
Self-report of dietary intake could be biased by social desirability or social approval thus affecting risk estimates in epidemiological studies. These constructs produce response set biases, which are evident when testing in domains characterized by easily recognizable correct or desirable responses. Given the social and psychological value ascribed to diet, assessment methodologies used most commonly in epidemiological studies are particularly vulnerable to these biases. Social desirability and social approval biases were tested by comparing nutrient scores derived from multiple 24-hour diet recalls (24HR) on seven randomly assigned days with those from two 7-day diet recalls (7DDR) (similar in some respects to commonly used food frequency questionnaires), one administered at the beginning of the test period (pre) and one at the end (post). Statistical analysis included correlation and multiple linear regression. Cross-sectionally, no relationships between social approval score and the nutritional variables existed. Social desirability score was negatively correlated with most nutritional variables. In linear regression analysis, social desirability score produced a large downward bias in nutrient estimation in the 7DDR relative to the 24HR. For total energy, this bias equalled about 50 kcal/point on the social desirability scale or about 450 kcal over its interquartile range. The bias was approximately twice as large for women as for men and only about half as large in the post measures. Individuals having the highest 24HR-derived fat and total energy intake scores had the largest downward bias due to social desirability. We observed a large downward bias in reporting food intake related to social desirability score. These results are consistent with the theoretical constructs on which the hypothesis is based. The effect of social desirability bias is discussed in terms of its influence on epidemiological estimates of effect. Suggestions are made for future work
Forecaster Behaviour and Bias in Macroeconomic Forecasts
Roy Batchelor
2007-01-01
This paper documents the presence of systematic bias in the real GDP and inflation forecasts of private sector forecasters in the G7 economies in the years 1990â€“2005. The data come from the monthly Consensus Economics forecasting service, and bias is measured and tested for significance using parametric fixed effect panel regressions and nonparametric tests on accuracy ranks. We examine patterns across countries and forecasters to establish whether the bias reflects the inefficient use of i...
An inclusive taxonomy of behavioral biases
David Peón; Manel Antelo; Anxo Calvo-Silvosa
2017-01-01
This paper overviews the theoretical and empirical research on behavioral biases and their influence in the literature. To provide a systematic exposition, we present a unified framework that takes the reader through an original taxonomy, based on the reviews of relevant authors in the field. In particular, we establish three broad categories that may be distinguished: heuristics and biases; choices, values and frames; and social factors. We then describe the main biases within each category,...
Evaluation of bias and variance in low-count OSEM list mode reconstruction
International Nuclear Information System (INIS)
Jian, Y; Carson, R E; Planeta, B
2015-01-01
Statistical algorithms have been widely used in PET image reconstruction. The maximum likelihood expectation maximization reconstruction has been shown to produce bias in applications where images are reconstructed from a relatively small number of counts. In this study, image bias and variability in low-count OSEM reconstruction are investigated on images reconstructed with MOLAR (motion-compensation OSEM list-mode algorithm for resolution-recovery reconstruction) platform. A human brain ([ 11 C]AFM) and a NEMA phantom are used in the simulation and real experiments respectively, for the HRRT and Biograph mCT. Image reconstructions were repeated with different combinations of subsets and iterations. Regions of interest were defined on low-activity and high-activity regions to evaluate the bias and noise at matched effective iteration numbers (iterations × subsets). Minimal negative biases and no positive biases were found at moderate count levels and less than 5% negative bias was found using extremely low levels of counts (0.2 M NEC). At any given count level, other factors, such as subset numbers and frame-based scatter correction may introduce small biases (1–5%) in the reconstructed images. The observed bias was substantially lower than that reported in the literature, perhaps due to the use of point spread function and/or other implementation methods in MOLAR. (paper)
Obtaining zircaloy powder through hydriding
International Nuclear Information System (INIS)
Dupim, Ivaldete da Silva; Moreira, Joao M.L.
2009-01-01
Zirconium alloys are good options for the metal matrix in dispersion fuels for power reactors due to their low thermal neutron absorption cross-section, good corrosion resistance, good mechanical strength and high thermal conductivity. A necessary step for obtaining such fuels is producing Zr alloy powder for the metal matrix composite material. This article presents results from the Zircaloy-4 hydrogenation tests with the purpose to embrittle the alloy as a first step for comminuting. Several hydrogenation tests were performed and studied through thermogravimetric analysis. They included H 2 pressures of 25 and 50 kPa and temperatures ranging between from 20 to 670 deg C. X-ray diffraction analysis showed in the hydrogenated samples the predominant presence of ZrH 2 and some ZrO 2 . Some kinetics parameters for the Zircaloy-4 hydrogenation reaction were obtained: the time required to reach the equilibrium state at the dwell temperature was about 100 minutes; the hydrogenation rate during the heating process from 20 to 670 deg C was about 21 mg/h, and at constant temperature of 670 deg C, the hydride rate was about 1.15 mg/h. The hydrogenation rate is largest during the heating process and most of it occurs during this period. After hydrogenated, the samples could easily be comminuted indicating that this is a possible technology to obtain Zircaloy powder. The results show that only few minutes of hydrogenation are necessary to reach the hydride levels required for comminuting the Zircaloy. The final hydride stoichiometry was between 2.7 and 2.8 H for each Zr atom in the sample (author)
Evaluation of bias associated with high-multiplex, target-specific pre-amplification
Directory of Open Access Journals (Sweden)
Steven T. Okino
2016-01-01
Full Text Available We developed a novel PCR-based pre-amplification (PreAmp technology that can increase the abundance of over 350 target genes one million-fold. To assess potential bias introduced by PreAmp we utilized ERCC RNA reference standards, a model system that quantifies measurement error in RNA analysis. We assessed three types of bias: amplification bias, dynamic range bias and fold-change bias. We show that our PreAmp workflow introduces only minimal amplification and fold-change bias under stringent conditions. We do detect dynamic range bias if a target gene is highly abundant and PreAmp occurred for 16 or more PCR cycles; however, this type of bias is easily correctable. To assess PreAmp bias in a gene expression profiling experiment, we analyzed a panel of genes that are regulated during differentiation using the NTera2 stem cell model system. We find that results generated using PreAmp are similar to results obtained using standard qPCR (without the pre-amplification step. Importantly, PreAmp maintains patterns of gene expression changes across samples; the same biological insights would be derived from a PreAmp experiment as with a standard gene expression profiling experiment. We conclude that our PreAmp technology can facilitate analysis of extremely limited samples in gene expression quantification experiments.
"Fair Play": A Videogame Designed to Address Implicit Race Bias Through Active Perspective Taking.
Gutierrez, Belinda; Kaatz, Anna; Chu, Sarah; Ramirez, Dennis; Samson-Samuel, Clem; Carnes, Molly
2014-12-01
Having diverse faculty in academic health centers will help diversify the healthcare workforce and reduce health disparities. Implicit race bias is one factor that contributes to the underrepresentation of Black faculty. We designed the videogame "Fair Play" in which players assume the role of a Black graduate student named Jamal Davis. As Jamal, players experience subtle race bias while completing "quests" to obtain a science degree. We hypothesized that participants randomly assigned to play the game would have greater empathy for Jamal and lower implicit race bias than participants randomized to read narrative text describing Jamal's experience. University of Wisconsin-Madison graduate students were recruited via e-mail and randomly assigned to play "Fair Play" or read narrative text through an online link. Upon completion, participants took an Implicit Association Test to measure implicit bias and answered survey questions assessing empathy toward Jamal and awareness of bias. As hypothesized, gameplayers showed the least implicit bias but only when they also showed high empathy for Jamal (P=0.013). Gameplayers did not show greater empathy than text readers, and women in the text condition reported the greatest empathy for Jamal (P=0.008). However, high empathy only predicted lower levels of implicit bias among those who actively took Jamal's perspective through gameplay (P=0.014). A videogame in which players experience subtle race bias as a Black graduate student has the potential to reduce implicit bias, possibly because of a game's ability to foster empathy through active perspective taking.
Cognitive Biases and Nonverbal Cue Availability in Detecting Deception
Burgoon, Judee K.; Blair, J. Pete; Strom, Renee E.
2008-01-01
In potentially deceptive situations, people rely on mental shortcuts to help process information. These heuristic judgments are often biased and result in inaccurate assessments of sender veracity. Four such biases--truth bias, visual bias, demeanor bias, and expectancy violation bias--were examined in a judgment experiment that varied nonverbal…
Attribution bias and social anxiety in schizophrenia
Directory of Open Access Journals (Sweden)
Amelie M. Achim
2016-06-01
Full Text Available Studies on attribution biases in schizophrenia have produced mixed results, whereas such biases have been more consistently reported in people with anxiety disorders. Anxiety comorbidities are frequent in schizophrenia, in particular social anxiety disorder, which could influence their patterns of attribution biases. The objective of the present study was thus to determine if individuals with schizophrenia and a comorbid social anxiety disorder (SZ+ show distinct attribution biases as compared with individuals with schizophrenia without social anxiety (SZ− and healthy controls. Attribution biases were assessed with the Internal, Personal, and Situational Attributions Questionnaire in 41 individual with schizophrenia and 41 healthy controls. Results revealed the lack of the normal externalizing bias in SZ+, whereas SZ− did not significantly differ from healthy controls on this dimension. The personalizing bias was not influenced by social anxiety but was in contrast linked with delusions, with a greater personalizing bias in individuals with current delusions. Future studies on attribution biases in schizophrenia should carefully document symptom presentation, including social anxiety.
Biased lineups: sequential presentation reduces the problem.
Lindsay, R C; Lea, J A; Nosworthy, G J; Fulford, J A; Hector, J; LeVan, V; Seabrook, C
1991-12-01
Biased lineups have been shown to increase significantly false, but not correct, identification rates (Lindsay, Wallbridge, & Drennan, 1987; Lindsay & Wells, 1980; Malpass & Devine, 1981). Lindsay and Wells (1985) found that sequential lineup presentation reduced false identification rates, presumably by reducing reliance on relative judgment processes. Five staged-crime experiments were conducted to examine the effect of lineup biases and sequential presentation on eyewitness recognition accuracy. Sequential lineup presentation significantly reduced false identification rates from fair lineups as well as from lineups biased with regard to foil similarity, instructions, or witness attire, and from lineups biased in all of these ways. The results support recommendations that police present lineups sequentially.
National Statistical Commission and Indian Official Statistics
Indian Academy of Sciences (India)
Author Affiliations. T J Rao1. C. R. Rao Advanced Institute of Mathematics, Statistics and Computer Science (AIMSCS) University of Hyderabad Campus Central University Post Office, Prof. C. R. Rao Road Hyderabad 500 046, AP, India.
Ensemble stacking mitigates biases in inference of synaptic connectivity
Directory of Open Access Journals (Sweden)
Brendan Chambers
2018-03-01
Full Text Available A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches. Mapping the routing of spikes through local circuitry is crucial for understanding neocortical computation. Under appropriate experimental conditions, these maps can be used to infer likely patterns of synaptic recruitment, linking activity to underlying anatomical connections. Such inferences help to reveal the synaptic implementation of population dynamics and computation. We compare a number of standard functional measures to infer underlying connectivity. We find that regularization impacts measures
Biasing secondary particle interaction physics and production in MCNP6
International Nuclear Information System (INIS)
Fensin, M.L.; James, M.R.
2016-01-01
Highlights: • Biasing secondary production and interactions of charged particles in the tabular energy regime. • Examining lower weight window bounds for rare events when using Russian roulette. • The new biasing strategy can speedup calculations by a factor of 1 million or more. - Abstract: Though MCNP6 will transport elementary charged particles and light ions to low energies (i.e. less than 20 MeV), MCNP6 has historically relied on model physics with suggested minimum energies of ∼20 to 200 MeV. Use of library data for the low energy regime was developed for MCNP6 1.1.Beta to read and use light ion libraries. Thick target yields of neutron production for alphas on fluoride result in 1 production event per roughly million sampled alphas depending on the energy of the alpha (for other isotopes the yield can be even rarer). Calculation times to achieve statistically significant and converged thick target yields are quite laborious, needing over one hundred processor hours. The MUCEND code possess a biasing technique for improving the sampling of secondary particle production by forcing a nuclear interaction to occur per each alpha transported. We present here a different biasing strategy for secondary particle production from charged particles. During each substep, as the charged particle slows down, we bias both a nuclear collision event to occur at each substep and the production of secondary particles at the collision event, while still continuing to progress the charged particle until reaching a region of zero importance or an energy/time cutoff. This biasing strategy is capable of speeding up calculations by a factor of a million or more as compared to the unbiased calculation. Further presented here are both proof that the biasing strategy is capable of producing the same results as the unbiased calculation and the limitations to consider in order to achieve accurate results of secondary particle production. Though this strategy was developed for MCNP
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
Industrial statistics with Minitab
Cintas, Pere Grima; Llabres, Xavier Tort-Martorell
2012-01-01
Industrial Statistics with MINITAB demonstrates the use of MINITAB as a tool for performing statistical analysis in an industrial context. This book covers introductory industrial statistics, exploring the most commonly used techniques alongside those that serve to give an overview of more complex issues. A plethora of examples in MINITAB are featured along with case studies for each of the statistical techniques presented. Industrial Statistics with MINITAB: Provides comprehensive coverage of user-friendly practical guidance to the essential statistical methods applied in industry.Explores
Statistical Methods for Fuzzy Data
Viertl, Reinhard
2011-01-01
Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy m
Testing human sperm chemotaxis: how to detect biased motion in population assays.
Directory of Open Access Journals (Sweden)
Leah Armon
Full Text Available Biased motion of motile cells in a concentration gradient of a chemoattractant is frequently studied on the population level. This approach has been particularly employed in human sperm chemotactic assays, where the fraction of responsive cells is low and detection of biased motion depends on subtle differences. In these assays, statistical measures such as population odds ratios of swimming directions can be employed to infer chemotactic performance. Here, we report on an improved method to assess statistical significance of experimentally determined odds ratios and discuss the strong impact of data correlations that arise from the directional persistence of sperm swimming.
Directory of Open Access Journals (Sweden)
Maddalena Marini
Full Text Available Although a greater degree of personal obesity is associated with weaker negativity toward overweight people on both explicit (i.e., self-report and implicit (i.e., indirect behavioral measures, overweight people still prefer thin people on average. We investigated whether the national and cultural context - particularly the national prevalence of obesity - predicts attitudes toward overweight people independent of personal identity and weight status. Data were collected from a total sample of 338,121 citizens from 71 nations in 22 different languages on the Project Implicit website (https://implicit.harvard.edu/ between May 2006 and October 2010. We investigated the relationship of the explicit and implicit weight bias with the obesity both at the individual (i.e., across individuals and national (i.e., across nations level. Explicit weight bias was assessed with self-reported preference between overweight and thin people; implicit weight bias was measured with the Implicit Association Test (IAT. The national estimates of explicit and implicit weight bias were obtained by averaging the individual scores for each nation. Obesity at the individual level was defined as Body Mass Index (BMI scores, whereas obesity at the national level was defined as three national weight indicators (national BMI, national percentage of overweight and underweight people obtained from publicly available databases. Across individuals, greater degree of obesity was associated with weaker implicit negativity toward overweight people compared to thin people. Across nations, in contrast, a greater degree of national obesity was associated with stronger implicit negativity toward overweight people compared to thin people. This result indicates a different relationship between obesity and implicit weight bias at the individual and national levels.
Noise Induces Biased Estimation of the Correction Gain.
Directory of Open Access Journals (Sweden)
Jooeun Ahn
Full Text Available The detection of an error in the motor output and the correction in the next movement are critical components of any form of motor learning. Accordingly, a variety of iterative learning models have assumed that a fraction of the error is adjusted in the next trial. This critical fraction, the correction gain, learning rate, or feedback gain, has been frequently estimated via least-square regression of the obtained data set. Such data contain not only the inevitable noise from motor execution, but also noise from measurement. It is generally assumed that this noise averages out with large data sets and does not affect the parameter estimation. This study demonstrates that this is not the case and that in the presence of noise the conventional estimate of the correction gain has a significant bias, even with the simplest model. Furthermore, this bias does not decrease with increasing length of the data set. This study reveals this limitation of current system identification methods and proposes a new method that overcomes this limitation. We derive an analytical form of the bias from a simple regression method (Yule-Walker and develop an improved identification method. This bias is discussed as one of other examples for how the dynamics of noise can introduce significant distortions in data analysis.
Torres, Felipe; Morales, Rafael; Schuller, Ivan K; Kiwi, Miguel
2017-11-09
The discovery of dipole-induced exchange bias (EB), switching from negative to positive sign, is reported in systems where the antiferromagnet and the ferromagnet are separated by a paramagnetic spacer (AFM-PM-FM). The magnitude and sign of the EB is determined by the cooling field strength and the PM thickness. The same cooling field yields negative EB for thin spacers, and positive EB for thicker ones. The EB decay profile as a function of the spacer thickness, and the change of sign, are attributed to long-ranged dipole coupling. Our model, which accounts quantitatively for the experimental results, ignores the short range interfacial exchange interactions of the usual EB theories. Instead, it retains solely the long range dipole field that allows for the coupling of the FM and AFM across the PM spacer. The experiments allow for novel switching capabilities of long range EB systems, while the theory allows description of the structures where the FM and AFM are not in atomic contact. The results provide a new approach to design novel interacting heterostructures.
Polypropylene obtained through zeolite supported catalysts
International Nuclear Information System (INIS)
Bastos, Queli C.; Marques, Maria de Fatima V.
2004-01-01
Propylene polymerizations were carried out with φ 2 C(Flu)(Cp)ZrCl 2 and SiMe 2 (Ind)2ZrCl 2 catalysts supported on silica, zeolite sodic mordenite (NaM) and acid mordenite (HM). The polymerizations were performed at different temperatures and varying aluminium/zirconium molar ratios ([Al]/[Zr]). The effect of these reaction parameters on the catalyst activity was investigated using a proposed statistical experimental planning. In the case of f 2 C(Flu)(Cp)ZrCl 2 , SiO 2 and NaM were used as support and the catalyst performance evaluated using toluene and pentane as polymerization solvent. The molecular weight, molecular weight distribution, melting point and crystallinity of the polymers were examined. The results indicate very high activities for the syndiospecific heterogeneous system. Also, the polymers obtained had superior Mw and stereo regularity. (author)
Polypropylene obtained through zeolite supported catalysts
Directory of Open Access Journals (Sweden)
Queli C. Bastos
2004-01-01
Full Text Available Propylene polymerizations were carried out with f2C(Flu(CpZrCl2 and SiMe2(Ind2ZrCl2 catalysts supported on silica, zeolite sodic mordenite (NaM and acid mordenite (HM. The polymerizations were performed at different temperatures and varying aluminium/zirconium molar ratios ([Al]/[Zr]. The effect of these reaction parameters on the catalyst activity was investigated using a proposed statistical experimental planning. In the case of f2C(Flu(CpZrCl2, SiO2 and NaM were used as support and the catalyst performance evaluated using toluene and pentane as polymerization solvent. The molecular weight, molecular weight distribution, melting point and crystallinity of the polymers were examined. The results indicate very high activities for the syndiospecific heterogeneous system. Also, the polymers obtained had superior Mw and stereoregularity.
Lorenz, Manuel; Bliefernicht, Jan; Laux, Patrick; Kunstmann, Harald
2017-04-01
Reliable estimates of future climatic conditions are indispensable for the sustainable planning of agricultural activities in West Africa. Precipitation time series of regional climate models (RCMs) typically exhibit a bias in the distribution of both rainfall intensities and wet day frequencies. Furthermore, the annual and monthly sums of precipitation may remarkably vary from the observations in this region. As West Africa experiences a distinct rainy season, sowing dates are oftentimes planned based on the beginning of this rainfall period. A biased representation of the annual cycle of precipitation in the uncorrected RCMs can therefore lead to crop failure. The precipitation ensemble, obtained from the Coordinated Downscaling Experiment CORDEX-Africa, was bias-corrected for the study region in West Africa (extending approximately 343,358 km2) which covers large parts of Burkina Faso, Ghana and Benin. In oder to debias the RCM precipitation simulations, a Quantile-Mapping method was applied to the historical period 1950-2005. For the RCM future projections (2006-2100), the Double-Quantile-Mapping procedure was chosen. This method makes use of the shift in the distribution function of the future precipitation values which allows to incorporate the climate change signal of the RCM projections into the bias correction. As large areas of the study region are ungauged, the assignment of the information from the nearest station to the ungauged location would lead to sharp changes in the estimated statistics from one location to another. Thus, the distribution parameters needed for the Quantile-Mapping were estimated by Kriging the distribution parameters of the available measurement stations. This way it is possible to obtain reasonable estimates of the expected distribution of precipitation at ungauged locations. The presentation will illustrate some aspects and trade-offs in the distribution parameter interpolation as well as an analysis of the uncertainties of the
Cheng, Dunlei; Branscum, Adam J; Stamey, James D
2010-07-01
To quantify the impact of ignoring misclassification of a response variable and measurement error in a covariate on statistical power, and to develop software for sample size and power analysis that accounts for these flaws in epidemiologic data. A Monte Carlo simulation-based procedure is developed to illustrate the differences in design requirements and inferences between analytic methods that properly account for misclassification and measurement error to those that do not in regression models for cross-sectional and cohort data. We found that failure to account for these flaws in epidemiologic data can lead to a substantial reduction in statistical power, over 25% in some cases. The proposed method substantially reduced bias by up to a ten-fold margin compared to naive estimates obtained by ignoring misclassification and mismeasurement. We recommend as routine practice that researchers account for errors in measurement of both response and covariate data when determining sample size, performing power calculations, or analyzing data from epidemiological studies. 2010 Elsevier Inc. All rights reserved.
Media bias under direct and indirect government control: when is the bias smaller?
Abhra Roy
2015-01-01
We present an analytical framework to compare media bias under direct and indirect government control. In this context, we show that direct control can lead to a smaller bias and higher welfare than indirect control. We further show that the size of the advertising market affects media bias only under direct control. Media bias, under indirect control, is not affected by the size of the advertising market.
Recreational Boating Statistics 2012
Department of Homeland Security — Every year, the USCG compiles statistics on reported recreational boating accidents. These statistics are derived from accident reports that are filed by the owners...
Recreational Boating Statistics 2013
Department of Homeland Security — Every year, the USCG compiles statistics on reported recreational boating accidents. These statistics are derived from accident reports that are filed by the owners...
Statistical data analysis handbook
National Research Council Canada - National Science Library
Wall, Francis J
1986-01-01
It must be emphasized that this is not a text book on statistics. Instead it is a working tool that presents data analysis in clear, concise terms which can be readily understood even by those without formal training in statistics...
U.S. Department of Health & Human Services — The CMS Office of Enterprise Data and Analytics has developed CMS Program Statistics, which includes detailed summary statistics on national health care, Medicare...
Recreational Boating Statistics 2011
Department of Homeland Security — Every year, the USCG compiles statistics on reported recreational boating accidents. These statistics are derived from accident reports that are filed by the owners...
... Doing AMIGAS Stay Informed Cancer Home Uterine Cancer Statistics Language: English (US) Español (Spanish) Recommend on Facebook ... the most commonly diagnosed gynecologic cancer. U.S. Cancer Statistics Data Visualizations Tool The Data Visualizations tool makes ...
Tuberculosis Data and Statistics
... Advisory Groups Federal TB Task Force Data and Statistics Language: English (US) Español (Spanish) Recommend on Facebook ... Set) Mortality and Morbidity Weekly Reports Data and Statistics Decrease in Reported Tuberculosis Cases MMWR 2010; 59 ( ...
National transportation statistics 2011
2011-04-01
Compiled and published by the U.S. Department of Transportation's Bureau of Transportation Statistics : (BTS), National Transportation Statistics presents information on the U.S. transportation system, including : its physical components, safety reco...
National Transportation Statistics 2008
2009-01-08
Compiled and published by the U.S. Department of Transportations Bureau of Transportation Statistics (BTS), National Transportation Statistics presents information on the U.S. transportation system, including its physical components, safety record...
... News & Events About Us Home > Health Information Share Statistics Research shows that mental illnesses are common in ... of mental illnesses, such as suicide and disability. Statistics Top ı cs Mental Illness Any Anxiety Disorder ...
School Violence: Data & Statistics
... Social Media Publications Injury Center School Violence: Data & Statistics Recommend on Facebook Tweet Share Compartir The first ... Vehicle Safety Traumatic Brain Injury Injury Response Data & Statistics (WISQARS) Funded Programs Press Room Social Media Publications ...
Caregiver Statistics: Demographics
... You are here Home Selected Long-Term Care Statistics Order this publication Printer-friendly version What is ... needs and services are wide-ranging and complex, statistics may vary from study to study. Sources for ...
... Summary Coverdell Program 2012-2015 State Summaries Data & Statistics Fact Sheets Heart Disease and Stroke Fact Sheets ... Roadmap for State Planning Other Data Resources Other Statistic Resources Grantee Information Cross-Program Information Online Tools ...
... Standard Drink? Drinking Levels Defined Alcohol Facts and Statistics Print version Alcohol Use in the United States: ... 1238–1245, 2004. PMID: 15010446 National Center for Statistics and Analysis. 2014 Crash Data Key Findings (Traffic ...
National Transportation Statistics 2009
2010-01-21
Compiled and published by the U.S. Department of Transportation's Bureau of Transportation Statistics (BTS), National Transportation Statistics presents information on the U.S. transportation system, including its physical components, safety record, ...
National transportation statistics 2010
2010-01-01
National Transportation Statistics presents statistics on the U.S. transportation system, including its physical components, safety record, economic performance, the human and natural environment, and national security. This is a large online documen...
DEFF Research Database (Denmark)
Lindström, Erik; Madsen, Henrik; Nielsen, Jan Nygaard
Statistics for Finance develops students’ professional skills in statistics with applications in finance. Developed from the authors’ courses at the Technical University of Denmark and Lund University, the text bridges the gap between classical, rigorous treatments of financial mathematics...
Principles of applied statistics
National Research Council Canada - National Science Library
Cox, D. R; Donnelly, Christl A
2011-01-01
.... David Cox and Christl Donnelly distil decades of scientific experience into usable principles for the successful application of statistics, showing how good statistical strategy shapes every stage of an investigation...
Full-counting statistics of energy transport of molecular junctions in the polaronic regime
International Nuclear Information System (INIS)
Tang, Gaomin; Yu, Zhizhou; Wang, Jian
2017-01-01
We investigate the full-counting statistics (FCS) of energy transport carried by electrons in molecular junctions for the Anderson–Holstein model in the polaronic regime. Using the two-time quantum measurement scheme, the generating function (GF) for the energy transport is derived and expressed as a Fredholm determinant in terms of Keldysh nonequilibrium Green’s function in the time domain. Dressed tunneling approximation is used in decoupling the phonon cloud operator in the polaronic regime. This formalism enables us to analyze the time evolution of energy transport dynamics after a sudden switch-on of the coupling between the dot and the leads towards the stationary state. The steady state energy current cumulant GF in the long time limit is obtained in the energy domain as well. Universal relations for steady state energy current FCS are derived under a finite temperature gradient with zero bias and this enabled us to express the equilibrium energy current cumulant by a linear combination of lower order cumulants. The behaviors of energy current cumulants in steady state under temperature gradient and external bias are numerically studied and explained. The transient dynamics of energy current cumulants is numerically calculated and analyzed. Universal scaling of normalized transient energy cumulants is found under both temperature gradient and external bias. (paper)
Kinnear, John; Jackson, Ruth
2017-07-01
Although physicians are highly trained in the application of evidence-based medicine, and are assumed to make rational decisions, there is evidence that their decision making is prone to biases. One of the biases that has been shown to affect accuracy of judgements is that of representativeness and base-rate neglect, where the saliency of a person's features leads to overestimation of their likelihood of belonging to a group. This results in the substitution of 'subjective' probability for statistical probability. This study examines clinicians' propensity to make estimations of subjective probability when presented with clinical information that is considered typical of a medical condition. The strength of the representativeness bias is tested by presenting choices in textual and graphic form. Understanding of statistical probability is also tested by omitting all clinical information. For the questions that included clinical information, 46.7% and 45.5% of clinicians made judgements of statistical probability, respectively. Where the question omitted clinical information, 79.9% of clinicians made a judgement consistent with statistical probability. There was a statistically significant difference in responses to the questions with and without representativeness information (χ2 (1, n=254)=54.45, pprobability. One of the causes for this representativeness bias may be the way clinical medicine is taught where stereotypic presentations are emphasised in diagnostic decision making. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Applying contemporary statistical techniques
Wilcox, Rand R
2003-01-01
Applying Contemporary Statistical Techniques explains why traditional statistical methods are often inadequate or outdated when applied to modern problems. Wilcox demonstrates how new and more powerful techniques address these problems far more effectively, making these modern robust methods understandable, practical, and easily accessible.* Assumes no previous training in statistics * Explains how and why modern statistical methods provide more accurate results than conventional methods* Covers the latest developments on multiple comparisons * Includes recent advanc
Developmental Changes in the Whole Number Bias
Braithwaite, David W.; Siegler, Robert S.
2018-01-01
Many students' knowledge of fractions is adversely affected by whole number bias, the tendency to focus on the separate whole number components (numerator and denominator) of a fraction rather than on the fraction's magnitude (ratio of numerator to denominator). Although whole number bias appears early in the fraction learning process and under…
Bounding the bias of contrastive divergence learning
DEFF Research Database (Denmark)
Fischer, Anja; Igel, Christian
2011-01-01
Optimization based on k-step contrastive divergence (CD) has become a common way to train restricted Boltzmann machines (RBMs). The k-step CD is a biased estimator of the log-likelihood gradient relying on Gibbs sampling. We derive a new upper bound for this bias. Its magnitude depends on k...
Distinctive Characteristics of Sexual Orientation Bias Crimes
Stacey, Michele
2011-01-01
Despite increased attention in the area of hate crime research in the past 20 years, sexual orientation bias crimes have rarely been singled out for study. When these types of crimes are looked at, the studies are typically descriptive in nature. This article seeks to increase our knowledge of sexual orientation bias by answering the question:…
Dialogue Games for Inconsistent and Biased Information
Lebbink, H.J.; Witteman, C.L.M.; Meyer, J.J.C.
2003-01-01
In this article, a dialogue game is presented in which coherent conversational sequences with inconsistent and biased information are described at the speech act level. Inconsistent and biased information is represented with bilattice structures, and based on these bilattice structures, a
Gender Bias: Inequities in the Classroom.
Love, Reeve
1993-01-01
This article explores sex bias in curricular materials for elementary and secondary schools. Sex bias is defined as a set of unconscious behaviors that, in themselves, are often trivial and generally favorable. Although these behaviors do not hurt if they happen only once, they can cause a great deal of harm if a pattern develops that serves to…
The Battle over Studies of Faculty Bias
Gravois, John
2007-01-01
The American Federation of Teachers (AFT) recently commissioned a study to review the research that finds liberal bias run amok in academe. Believing that the AFT is not a dispassionate observer of this debate, this article provides "The Chronicle of Higher Education's" survey of the genre. The studies reviewed include: (1) "Political Bias in the…
Interactive statistics with ILLMO
Martens, J.B.O.S.
2014-01-01
Progress in empirical research relies on adequate statistical analysis and reporting. This article proposes an alternative approach to statistical modeling that is based on an old but mostly forgotten idea, namely Thurstone modeling. Traditional statistical methods assume that either the measured
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…
Youth Sports Safety Statistics
... 6):794-799. 31 American Heart Association. CPR statistics. www.heart.org/HEARTORG/CPRAndECC/WhatisCPR/CPRFactsandStats/CPRpercent20Statistics_ ... Mental Health Services Administration, Center for Behavioral Health Statistics and Quality. (January 10, 2013). The DAWN Report: ...
Guo, Shaoyin; Hihath, Joshua; Díez-Pérez, Ismael; Tao, Nongjian
2011-11-30
We report on the measurement and statistical study of thousands of current-voltage characteristics and transition voltage spectra (TVS) of single-molecule junctions with different contact geometries that are rapidly acquired using a new break junction method at room temperature. This capability allows one to obtain current-voltage, conductance voltage, and transition voltage histograms, thus adding a new dimension to the previous conductance histogram analysis at a fixed low-bias voltage for single molecules. This method confirms the low-bias conductance values of alkanedithiols and biphenyldithiol reported in literature. However, at high biases the current shows large nonlinearity and asymmetry, and TVS allows for the determination of a critically important parameter, the tunneling barrier height or energy level alignment between the molecule and the electrodes of single-molecule junctions. The energy level alignment is found to depend on the molecule and also on the contact geometry, revealing the role of contact geometry in both the contact resistance and energy level alignment of a molecular junction. Detailed statistical analysis further reveals that, despite the dependence of the energy level alignment on contact geometry, the variation in single-molecule conductance is primarily due to contact resistance rather than variations in the energy level alignment.
Directory of Open Access Journals (Sweden)
Zhitao Niu
2017-11-01
Full Text Available The variation of GC content is a key genome feature because it is associated with fundamental elements of genome organization. However, the reason for this variation is still an open question. Different kinds of hypotheses have been proposed to explain the variation of GC content during genome evolution. However, these hypotheses have not been explicitly investigated in whole plastome sequences. Dendrobium is one of the largest genera in the orchid species. Evolutionary studies of the plastomic organization and base composition are limited in this genus. In this study, we obtained the high-quality plastome sequences of D. loddigesii and D. devonianum. The comparison results showed a nearly identical organization in Dendrobium plastomes, indicating that the plastomic organization is highly conserved in Dendrobium genus. Furthermore, the impact of three evolutionary forces—selection, mutational biases, and GC-biased gene conversion (gBGC—on the variation of GC content in Dendrobium plastomes was evaluated. Our results revealed: (1 consistent GC content evolution trends and mutational biases in single-copy (SC and inverted repeats (IRs regions; and (2 that gBGC has influenced the plastome-wide GC content evolution. These results suggest that both mutational biases and gBGC affect GC content in the plastomes of Dendrobium genus.
Niu, Zhitao; Xue, Qingyun; Wang, Hui; Xie, Xuezhu; Zhu, Shuying; Liu, Wei; Ding, Xiaoyu
2017-01-01
The variation of GC content is a key genome feature because it is associated with fundamental elements of genome organization. However, the reason for this variation is still an open question. Different kinds of hypotheses have been proposed to explain the variation of GC content during genome evolution. However, these hypotheses have not been explicitly investigated in whole plastome sequences. Dendrobium is one of the largest genera in the orchid species. Evolutionary studies of the plastomic organization and base composition are limited in this genus. In this study, we obtained the high-quality plastome sequences of D. loddigesii and D. devonianum. The comparison results showed a nearly identical organization in Dendrobium plastomes, indicating that the plastomic organization is highly conserved in Dendrobium genus. Furthermore, the impact of three evolutionary forces—selection, mutational biases, and GC-biased gene conversion (gBGC)—on the variation of GC content in Dendrobium plastomes was evaluated. Our results revealed: (1) consistent GC content evolution trends and mutational biases in single-copy (SC) and inverted repeats (IRs) regions; and (2) that gBGC has influenced the plastome-wide GC content evolution. These results suggest that both mutational biases and gBGC affect GC content in the plastomes of Dendrobium genus. PMID:29099062
Development and application of the automated Monte Carlo biasing procedure in SAS4
International Nuclear Information System (INIS)
Tang, J.S.; Broadhead, B.L.
1993-01-01
An automated approach for biasing Monte Carlo shielding calculations is described. In particular, adjoint fluxes from a one-dimensional discrete-ordinates calculation are used to generate biasing parameters for a three-dimensional Monte Carlo calculation. The automated procedure consisting of cross-section processing, adjoint flux determination, biasing parameter generation, and the initiation of a MORSE-SGC/S Monte Carlo calculation has been implemented in the SAS4 module of the SCALE computer code system. The automated procedure has been used extensively in the investigation of both computational and experimental benchmarks for the NEACRP working group on shielding assessment of transportation packages. The results of these studies indicate that with the automated biasing procedure, Monte Carlo shielding calculations of spent fuel casks can be easily performed with minimum effort and that accurate results can be obtained at reasonable computing cost. The systematic biasing approach described in this paper can also be applied to other similar shielding problems
Production bias and cluster annihilation: Why necessary?
DEFF Research Database (Denmark)
Singh, B.N.; Trinkaus, H.; Woo, C.H.
1994-01-01
the primary cluster density is high. Therefore, a sustained high swelling rate driven by production bias must involve the annihilation of primary clusters at sinks. A number of experimental observations which are unexplainable in terms of the conventional dislocation bias for monointerstitials is considered......-field approach. The production bias approach, on the other hand, is based on the physical features of the cascade damage and is therefore considered to be more appropriate for describing the damage accumulation under cascade damage conditions. However, production bias can not produce high a swelling rate when....... It is found that the production bias and cluster annihilation are necessary to explain these observations, with, in many cases, the explicit consideration of the annihilation of the primary interstitial clusters....
Gender bias in cardiovascular advertisements.
Ahmed, Sofia B; Grace, Sherry L; Stelfox, Henry Thomas; Tomlinson, George; Cheung, Angela M
2004-11-01
Women with cardiovascular disease are treated less aggressively than men. The reasons for this disparity are unclear. Pharmaceutical advertisements may influence physician practices and patient care. To determine if female and male patients are equally likely to be featured in cardiovascular advertisements. We examined all cardiovascular advertisements from US editions of general medical and cardiovascular journals published between 1 January 1996 and 30 June 1998. For each unique advertisement, we recorded the total number of journal appearances and the number of appearances in journals' premium positions. We noted the gender, age, race and role of both the primary figure and the majority of people featured in the advertisement. Nine hundred and nineteen unique cardiovascular advertisements were identified of which 254 depicted a patient as the primary figure. A total of 20%[95% confidence interval (CI) 15.3-25.5%] of these advertisements portrayed a female patient, while 80% (95% CI 74.5-84.7%) depicted a male patient, P advertisements appeared 249 times (13.3%; 95% CI 8.6-18.9%) while male patient advertisements appeared 1618 times (86.7%; 95% CI 81.1-91.4%), P advertisements also had significantly fewer mean appearances than male patient advertisements in journals' premium positions (0.82 vs. 1.99, P=0.02). Similar results were seen when the advertisements were analysed according to predominant gender. Despite increasing emphasis on cardiovascular disease in women, significant under-representation of female patients exists in cardiovascular advertisements. Physicians should be cognizant of this gender bias.
Drugs obtained by biotechnology processing
Directory of Open Access Journals (Sweden)
Hugo Almeida
2011-06-01
Full Text Available In recent years, the number of drugs of biotechnological origin available for many different diseases has increased exponentially, including different types of cancer, diabetes mellitus, infectious diseases (e.g. AIDS Virus / HIV as well as cardiovascular, neurological, respiratory, and autoimmune diseases, among others. The pharmaceutical industry has used different technologies to obtain new and promising active ingredients, as exemplified by the fermentation technique, recombinant DNA technique and the hybridoma technique. The expiry of the patents of the first drugs of biotechnological origin and the consequent emergence of biosimilar products, have posed various questions to health authorities worldwide regarding the definition, framework, and requirements for authorization to market such products.Nos últimos anos, tem aumentado exponencialmente o número de fármacos de origem biotecnológica ao dispor das mais diversas patologias, entre elas destacam-se, os diferentes tipos de cancêr, as doenças infecciosas (ex. vírus AIDS/HIV, as doenças autoimunes, as doenças cardiovasculares, a Diabetes Mellitus, as doenças neurológicas, as doenças respiratórias, entre outras. A indústria farmacêutica tem recorrido a diferentes tecnologias para a obtenção de novos e promissores princípios ativos, como são exemplo a fermentação, a técnica de DNA Recombinante, a técnica de hidridoma, entre outras. A queda das patentes dos primeiros fármacos de origem biotecnológica e o consequente aparecimento dos produtos biossimilares têm colocado diferentes questões às autoridades de saúde mundiais, sobre a definição, enquadramento e exigências para a autorização de entrada no mercado deste tipo de produtos.
A Climate Statistics Tool and Data Repository
Wang, J.; Kotamarthi, V. R.; Kuiper, J. A.; Orr, A.
2017-12-01
Researchers at Argonne National Laboratory and collaborating organizations have generated regional scale, dynamically downscaled climate model output using Weather Research and Forecasting (WRF) version 3.3.1 at a 12km horizontal spatial resolution over much of North America. The WRF model is driven by boundary conditions obtained from three independent global scale climate models and two different future greenhouse gas emission scenarios, named representative concentration pathways (RCPs). The repository of results has a temporal resolution of three hours for all the simulations, includes more than 50 variables, is stored in Network Common Data Form (NetCDF) files, and the data volume is nearly 600Tb. A condensed 800Gb set of NetCDF files were made for selected variables most useful for climate-related planning, including daily precipitation, relative humidity, solar radiation, maximum temperature, minimum temperature, and wind. The WRF model simulations are conducted for three 10-year time periods (1995-2004, 2045-2054, and 2085-2094), and two future scenarios RCP4.5 and RCP8.5). An open-source tool was coded using Python 2.7.8 and ESRI ArcGIS 10.3.1 programming libraries to parse the NetCDF files, compute summary statistics, and output results as GIS layers. Eight sets of summary statistics were generated as examples for the contiguous U.S. states and much of Alaska, including number of days over 90°F, number of days with a heat index over 90°F, heat waves, monthly and annual precipitation, drought, extreme precipitation, multi-model averages, and model bias. This paper will provide an overview of the project to generate the main and condensed data repositories, describe the Python tool and how to use it, present the GIS results of the computed examples, and discuss some of the ways they can be used for planning. The condensed climate data, Python tool, computed GIS results, and documentation of the work are shared on the Internet.
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
Boslaugh, Sarah
2013-01-01
Need to learn statistics for your job? Want help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference for anyone new to the subject. Thoroughly revised and expanded, this edition helps you gain a solid understanding of statistics without the numbing complexity of many college texts. Each chapter presents easy-to-follow descriptions, along with graphics, formulas, solved examples, and hands-on exercises. If you want to perform common statistical analyses and learn a wide range of techniques without getting in over your head, this is your book.
Statistics & probaility for dummies
Rumsey, Deborah J
2013-01-01
Two complete eBooks for one low price! Created and compiled by the publisher, this Statistics I and Statistics II bundle brings together two math titles in one, e-only bundle. With this special bundle, you'll get the complete text of the following two titles: Statistics For Dummies, 2nd Edition 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. Tra
Nonparametric statistical inference
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
Business statistics for dummies
Anderson, Alan
2013-01-01
Score higher in your business statistics course? Easy. Business statistics is a common course for business majors and MBA candidates. It examines common data sets and the proper way to use such information when conducting research and producing informational reports such as profit and loss statements, customer satisfaction surveys, and peer comparisons. Business Statistics For Dummies tracks to a typical business statistics course offered at the undergraduate and graduate levels and provides clear, practical explanations of business statistical ideas, techniques, formulas, and calculations, w
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
No arousal-biased competition in focused visuospatial attention.
Ásgeirsson, Árni Gunnar; Nieuwenhuis, Sander
2017-11-01
Arousal sometimes enhances and sometimes impairs perception and memory. A recent theory attempts to reconcile these findings by proposing that arousal amplifies the competition between stimulus representations, strengthening already strong representations and weakening already weak representations. Here, we report a stringent test of this arousal-biased competition theory in the context of focused visuospatial attention. Participants were required to identify a briefly presented target in the context of multiple distractors, which varied in the degree to which they competed for representation with the target, as revealed by psychophysics. We manipulated arousal using emotionally arousing pictures (Experiment 1), alerting tones (Experiment 2) and white-noise stimulation (Experiment 3), and validated these manipulations with electroencephalography and pupillometry. In none of the experiments did we find evidence that arousal modulated the effect of distractor competition on the accuracy of target identification. Bayesian statistics revealed moderate to strong evidence against arousal-biased competition. Modeling of the psychophysical data based on Bundesen's (1990) theory of visual attention corroborated the conclusion that arousal does not bias competition in focused visuospatial attention. Copyright © 2017 Elsevier B.V. All rights reserved.
PEST reduces bias in forced choice psychophysics.
Taylor, M M; Forbes, S M; Creelman, C D
1983-11-01
Observers performed several different detection tasks using both the PEST adaptive psychophysical procedure and a fixed-level (method of constant stimuli) psychophysical procedure. In two experiments, PEST runs targeted at P (C) = 0.80 were immediately followed by fixed-level detection runs presented at the difficulty level resulting from the PEST run. The fixed-level runs yielded P (C) about 0.75. During the fixed-level runs, the probability of a correct response was greater when the preceding response was correct than when it was wrong. Observers, even highly trained ones, perform in a nonstationary manner. The sequential dependency data can be used to determine a lower bound for the observer's "true" capability when performing optimally; this lower bound is close to the PEST target, and well above the forced choice P (C). The observer's "true" capability is the measure used by most theories of detection performance. A further experiment compared psychometric functions obtained from a set of PEST runs using different targets with those obtained from blocks of fixed-level trials at different levels. PEST results were more stable across observers, performance at all but the highest signal levels was better with PEST, and the PEST psychometric functions had shallower slopes. We hypothesize that PEST permits the observer to keep track of what he is trying to detect, whereas in the fixed-level method performance is disrupted by memory failure. Some recently suggested "more virulent" versions of PEST may be subject to biases similar to those of the fixed-level procedures.(ABSTRACT TRUNCATED AT 250 WORDS)
Lectures on algebraic statistics
Drton, Mathias; Sullivant, Seth
2009-01-01
How does an algebraic geometer studying secant varieties further the understanding of hypothesis tests in statistics? Why would a statistician working on factor analysis raise open problems about determinantal varieties? Connections of this type are at the heart of the new field of "algebraic statistics". In this field, mathematicians and statisticians come together to solve statistical inference problems using concepts from algebraic geometry as well as related computational and combinatorial techniques. The goal of these lectures is to introduce newcomers from the different camps to algebraic statistics. The introduction will be centered around the following three observations: many important statistical models correspond to algebraic or semi-algebraic sets of parameters; the geometry of these parameter spaces determines the behaviour of widely used statistical inference procedures; computational algebraic geometry can be used to study parameter spaces and other features of statistical models.
Magnification bias corrections to galaxy-lensing cross-correlations
International Nuclear Information System (INIS)
Ziour, Riad; Hui, Lam
2008-01-01
Galaxy-galaxy or galaxy-quasar lensing can provide important information on the mass distribution in the Universe. It consists of correlating the lensing signal (either shear or magnification) of a background galaxy/quasar sample with the number density of a foreground galaxy sample. However, the foreground galaxy density is inevitably altered by the magnification bias due to the mass between the foreground and the observer, leading to a correction to the observed galaxy-lensing signal. The aim of this paper is to quantify this correction. The single most important determining factor is the foreground redshift z f : the correction is small if the foreground galaxies are at low redshifts but can become non-negligible for sufficiently high redshifts. For instance, we find that for the multipole l=1000, the correction is above 1%x(5s f -2)/b f for z f > or approx. 0.37, and above 5%x(5s f -2)/b f for z f > or approx. 0.67, where s f is the number count slope of the foreground sample and b f its galaxy bias. These considerations are particularly important for geometrical measures, such as the Jain and Taylor ratio or its generalization by Zhang et al. Assuming (5s f -2)/b f =1, we find that the foreground redshift should be limited to z f < or approx. 0.45 in order to avoid biasing the inferred dark energy equation of state w by more than 5%, and that even for a low foreground redshift (<0.45), the background samples must be well separated from the foreground to avoid incurring a bias of similar magnitude. Lastly, we briefly comment on the possibility of obtaining these geometrical measures without using galaxy shapes, using instead magnification bias itself.
Gender bias in primary education a theoretical analysis
Directory of Open Access Journals (Sweden)
Róbert Osaďan
2013-11-01
Full Text Available For decades, gender bias and inequity have remained extensive issues in nearly all societies in the world. During the past years, the effects of these issues have extended to one of the most important facets in our society - the education sector. Although this may not be immediately shocking, a lot of researchers as well as concerned educators and parents believe otherwise. As a matter of fact, a myriad of studies and research projects have already proven that gender discrimination, bias, and other related issues in sexuality actually exist in most primary schools throughout the globe. These literary materials present vital points that provide the initiative for primary school educators, school administrators, and other parents to become aware of the gender issues, which significantly affect the school performance and achievement of the concerned students, most of them being girls. Also, a number of studies have identified gender bias agents and their contributions in the worsening of the problem. Obviously, this problem needs to be addressed by the people most empowered - the educators. There is no question whether or not primary school teachers possess the knowledge to circumvent this bias inside their classrooms. The true concern is when they will actually start to apply crucial measures to resolve and get rid of gender bias. Once they eliminate their own prejudices about their students in terms of gender- related issues, they will be able to provide each of their pupils the right and proper education that the children deserve to get. And if all students obtain fair educational treatment, academic excellence and competence will merely be two of the countless benefits they can get.
Baseline Statistics of Linked Statistical Data
Scharnhorst, Andrea; Meroño-Peñuela, Albert; Guéret, Christophe
2014-01-01
We are surrounded by an ever increasing ocean of information, everybody will agree to that. We build sophisticated strategies to govern this information: design data models, develop infrastructures for data sharing, building tool for data analysis. Statistical datasets curated by National
Fundamentals of statistical signal processing
Kay, Steven M
1993-01-01
A unified presentation of parameter estimation for those involved in the design and implementation of statistical signal processing algorithms. Covers important approaches to obtaining an optimal estimator and analyzing its performance; and includes numerous examples as well as applications to real- world problems. MARKETS: For practicing engineers and scientists who design and analyze signal processing systems, i.e., to extract information from noisy signals — radar engineer, sonar engineer, geophysicist, oceanographer, biomedical engineer, communications engineer, economist, statistician, physicist, etc.
Statistical analysis of environmental data
International Nuclear Information System (INIS)
Beauchamp, J.J.; Bowman, K.O.; Miller, F.L. Jr.
1975-10-01
This report summarizes the analyses of data obtained by the Radiological Hygiene Branch of the Tennessee Valley Authority from samples taken around the Browns Ferry Nuclear Plant located in Northern Alabama. The data collection was begun in 1968 and a wide variety of types of samples have been gathered on a regular basis. The statistical analysis of environmental data involving very low-levels of radioactivity is discussed. Applications of computer calculations for data processing are described
Estimation of satellite position, clock and phase bias corrections
Henkel, Patrick; Psychas, Dimitrios; Günther, Christoph; Hugentobler, Urs
2018-05-01
Precise point positioning with integer ambiguity resolution requires precise knowledge of satellite position, clock and phase bias corrections. In this paper, a method for the estimation of these parameters with a global network of reference stations is presented. The method processes uncombined and undifferenced measurements of an arbitrary number of frequencies such that the obtained satellite position, clock and bias corrections can be used for any type of differenced and/or combined measurements. We perform a clustering of reference stations. The clustering enables a common satellite visibility within each cluster and an efficient fixing of the double difference ambiguities within each cluster. Additionally, the double difference ambiguities between the reference stations of different clusters are fixed. We use an integer decorrelation for ambiguity fixing in dense global networks. The performance of the proposed method is analysed with both simulated Galileo measurements on E1 and E5a and real GPS measurements of the IGS network. We defined 16 clusters and obtained satellite position, clock and phase bias corrections with a precision of better than 2 cm.
Variance bias analysis for the Gelbard's batch method
Energy Technology Data Exchange (ETDEWEB)
Seo, Jae Uk; Shim, Hyung Jin [Seoul National Univ., Seoul (Korea, Republic of)
2014-05-15
In this paper, variances and the bias will be derived analytically when the Gelbard's batch method is applied. And then, the real variance estimated from this bias will be compared with the real variance calculated from replicas. Variance and the bias were derived analytically when the batch method was applied. If the batch method was applied to calculate the sample variance, covariance terms between tallies which exist in the batch were eliminated from the bias. With the 2 by 2 fission matrix problem, we could calculate real variance regardless of whether or not the batch method was applied. However as batch size got larger, standard deviation of real variance was increased. When we perform a Monte Carlo estimation, we could get a sample variance as the statistical uncertainty of it. However, this value is smaller than the real variance of it because a sample variance is biased. To reduce this bias, Gelbard devised the method which is called the Gelbard's batch method. It has been certificated that a sample variance get closer to the real variance when the batch method is applied. In other words, the bias get reduced. This fact is well known to everyone in the MC field. However, so far, no one has given the analytical interpretation on it.
Effects of biases in domain wall network evolution. II. Quantitative analysis
Correia, J. R. C. C. C.; Leite, I. S. C. R.; Martins, C. J. A. P.
2018-04-01
Domain walls form at phase transitions which break discrete symmetries. In a cosmological context, they often overclose the Universe (contrary to observational evidence), although one may prevent this by introducing biases or forcing anisotropic evolution of the walls. In a previous work [Correia et al., Phys. Rev. D 90, 023521 (2014), 10.1103/PhysRevD.90.023521], we numerically studied the evolution of various types of biased domain wall networks in the early Universe, confirming that anisotropic networks ultimately reach scaling while those with a biased potential or biased initial conditions decay. We also found that the analytic decay law obtained by Hindmarsh was in good agreement with simulations of biased potentials, but not of biased initial conditions, and suggested that the difference was related to the Gaussian approximation underlying the analytic law. Here, we extend our previous work in several ways. For the cases of biased potential and biased initial conditions, we study in detail the field distributions in the simulations, confirming that the validity (or not) of the Gaussian approximation is the key difference between the two cases. For anisotropic walls, we carry out a more extensive set of numerical simulations and compare them to the canonical velocity-dependent one-scale model for domain walls, finding that the model accurately predicts the linear scaling regime after isotropization. Overall, our analysis provides a quantitative description of the cosmological evolution of these networks.
Vanderweele, Tyler J; Arah, Onyebuchi A
2011-01-01
Uncontrolled confounding in observational studies gives rise to biased effect estimates. Sensitivity analysis techniques can be useful in assessing the magnitude of these biases. In this paper, we use the potential outcomes framework to derive a general class of sensitivity-analysis formulas for outcomes, treatments, and measured and unmeasured confounding variables that may be categorical or continuous. We give results for additive, risk-ratio and odds-ratio scales. We show that these results encompass a number of more specific sensitivity-analysis methods in the statistics and epidemiology literature. The applicability, usefulness, and limits of the bias-adjustment formulas are discussed. We illustrate the sensitivity-analysis techniques that follow from our results by applying them to 3 different studies. The bias formulas are particularly simple and easy to use in settings in which the unmeasured confounding variable is binary with constant effect on the outcome across treatment levels.
A re-examination of the effects of biased lineup instructions in eyewitness identification.
Clark, Steven E
2005-10-01
A meta-analytic review of research comparing biased and unbiased instructions in eyewitness identification experiments showed an asymmetry; specifically, that biased instructions led to a large and consistent decrease in accuracy in target-absent lineups, but produced inconsistent results for target-present lineups, with an average effect size near zero (Steblay, 1997). The results for target-present lineups are surprising, and are inconsistent with statistical decision theories (i.e., Green & Swets, 1966). A re-examination of the relevant studies and the meta-analysis of those studies shows clear evidence that correct identification rates do increase with biased lineup instructions, and that biased witnesses make correct identifications at a rate considerably above chance. Implications for theory, as well as police procedure and policy, are discussed.
Automation bias in electronic prescribing.
Lyell, David; Magrabi, Farah; Raban, Magdalena Z; Pont, L G; Baysari, Melissa T; Day, Richard O; Coiera, Enrico
2017-03-16
Clinical decision support (CDS) in e-prescribing can improve safety by alerting potential errors, but introduces new sources of risk. Automation bias (AB) occurs when users over-rely on CDS, reducing vigilance in information seeking and processing. Evidence of AB has been found in other clinical tasks, but has not yet been tested with e-prescribing. This study tests for the presence of AB in e-prescribing and the impact of task complexity and interruptions on AB. One hundred and twenty students in the final two years of a medical degree prescribed medicines for nine clinical scenarios using a simulated e-prescribing system. Quality of CDS (correct, incorrect and no CDS) and task complexity (low, low + interruption and high) were varied between conditions. Omission errors (failure to detect prescribing errors) and commission errors (acceptance of false positive alerts) were measured. Compared to scenarios with no CDS, correct CDS reduced omission errors by 38.3% (p < .0001, n = 120), 46.6% (p < .0001, n = 70), and 39.2% (p < .0001, n = 120) for low, low + interrupt and high complexity scenarios respectively. Incorrect CDS increased omission errors by 33.3% (p < .0001, n = 120), 24.5% (p < .009, n = 82), and 26.7% (p < .0001, n = 120). Participants made commission errors, 65.8% (p < .0001, n = 120), 53.5% (p < .0001, n = 82), and 51.7% (p < .0001, n = 120). Task complexity and interruptions had no impact on AB. This study found evidence of AB omission and commission errors in e-prescribing. Verification of CDS alerts is key to avoiding AB errors. However, interventions focused on this have had limited success to date. Clinicians should remain vigilant to the risks of CDS failures and verify CDS.
Local sequence alignments statistics: deviations from Gumbel statistics in the rare-event tail
Directory of Open Access Journals (Sweden)
Burghardt Bernd
2007-07-01
Full Text Available Abstract Background The optimal score for ungapped local alignments of infinitely long random sequences is known to follow a Gumbel extreme value distribution. Less is known about the important case, where gaps are allowed. For this case, the distribution is only known empirically in the high-probability region, which is biologically less relevant. Results We provide a method to obtain numerically the biologically relevant rare-event tail of the distribution. The method, which has been outlined in an earlier work, is based on generating the sequences with a parametrized probability distribution, which is biased with respect to the original biological one, in the framework of Metropolis Coupled Markov Chain Monte Carlo. Here, we first present the approach in detail and evaluate the convergence of the algorithm by considering a simple test case. In the earlier work, the method was just applied to one single example case. Therefore, we consider here a large set of parameters: We study the distributions for protein alignment with different substitution matrices (BLOSUM62 and PAM250 and affine gap costs with different parameter values. In the logarithmic phase (large gap costs it was previously assumed that the Gumbel form still holds, hence the Gumbel distribution is usually used when evaluating p-values in databases. Here we show that for all cases, provided that the sequences are not too long (L > 400, a "modified" Gumbel distribution, i.e. a Gumbel distribution with an additional Gaussian factor is suitable to describe the data. We also provide a "scaling analysis" of the parameters used in the modified Gumbel distribution. Furthermore, via a comparison with BLAST parameters, we show that significance estimations change considerably when using the true distributions as presented here. Finally, we study also the distribution of the sum statistics of the k best alignments. Conclusion Our results show that the statistics of gapped and ungapped local
What price the spin–statistics theorem?
Indian Academy of Sciences (India)
phase factor must be +1, but there is no other reason to do so than to obtain the spin– statistics ... teristic antisymmetric time derivative terms and symmetric 'mass' terms. Hermiticity .... generalizes Bacry's picture in the way sought by Broyles.
Understanding search trees via statistical physics
Indian Academy of Sciences (India)
ary search tree model (where stands for the number of branches of the search tree), an important problem for data storage in computer science, using a variety of statistical physics techniques that allow us to obtain exact asymptotic results.
Stabilization of electron beam spot size by self bias potential
International Nuclear Information System (INIS)
Kwan, T.J.T.; Moir, D.C.; Snell, C.M.; Kang, M.
1998-01-01
In high resolution flash x-ray imaging technology the electric field developed between the electron beam and the converter target is large enough to draw ions from the target surface. The ions provide fractional neutralization and cause the electron beam to focus radially inward, and the focal point subsequently moves upstream due to the expansion of the ion column. A self-bias target concept is proposed and verified via computer simulation that the electron charge deposited on the target can generate an electric potential, which can effectively limit the ion motion and thereby stabilize the growth of the spot size. A target chamber using the self bias target concept was designed and tested in the Integrated Test Stand (ITS). The authors have obtained good agreement between computer simulation and experiment
Thygesen, Uffe Høgsbro
2016-03-01
We consider organisms which use a renewal strategy such as run-tumble when moving in space, for example to perform chemotaxis in chemical gradients. We derive a diffusion approximation for the motion, applying a central limit theorem due to Anscombe for renewal-reward processes; this theorem has not previously been applied in this context. Our results extend previous work, which has established the mean drift but not the diffusivity. For a classical model of tumble rates applied to chemotaxis, we find that the resulting chemotactic drift saturates to the swimming velocity of the organism when the chemical gradients grow increasingly steep. The dispersal becomes anisotropic in steep gradients, with larger dispersal across the gradient than along the gradient. In contrast to one-dimensional settings, strong bias increases dispersal. We next include Brownian rotation in the model and find that, in limit of high chemotactic sensitivity, the chemotactic drift is 64% of the swimming velocity, independent of the magnitude of the Brownian rotation. We finally derive characteristic timescales of the motion that can be used to assess whether the diffusion limit is justified in a given situation. The proposed technique for obtaining diffusion approximations is conceptually and computationally simple, and applicable also when statistics of the motion is obtained empirically or through Monte Carlo simulation of the motion.
Biases in GNSS-Data Processing
Schaer, S. C.; Dach, R.; Lutz, S.; Meindl, M.; Beutler, G.
2010-12-01
Within the Global Positioning System (GPS) traditionally different types of pseudo-range measurements (P-code, C/A-code) are available on the first frequency that are tracked by the receivers with different technologies. For that reason, P1-C1 and P1-P2 Differential Code Biases (DCB) need to be considered in a GPS data processing with a mix of different receiver types. Since the Block IIR-M series of GPS satellites also provide C/A-code on the second frequency, P2-C2 DCB need to be added to the list of biases for maintenance. Potential quarter-cycle biases between different phase observables (specifically L2P and L2C) are another issue. When combining GNSS (currently GPS and GLONASS), careful consideration of inter-system biases (ISB) is indispensable, in particular when an adequate combination of individual GLONASS clock correction results from different sources (using, e.g., different software packages) is intended. Facing the GPS and GLONASS modernization programs and the upcoming GNSS, like the European Galileo and the Chinese Compass, an increasing number of types of biases is expected. The Center for Orbit Determination in Europe (CODE) is monitoring these GPS and GLONASS related biases for a long time based on RINEX files of the tracking network of the International GNSS Service (IGS) and in the frame of the data processing as one of the global analysis centers of the IGS. Within the presentation we give an overview on the stability of the biases based on the monitoring. Biases derived from different sources are compared. Finally, we give an outlook on the potential handling of such biases with the big variety of signals and systems expected in the future.
Sampling bias in an internet treatment trial for depression.
Donkin, L; Hickie, I B; Christensen, H; Naismith, S L; Neal, B; Cockayne, N L; Glozier, N
2012-10-23
Internet psychological interventions are efficacious and may reduce traditional access barriers. No studies have evaluated whether any sampling bias exists in these trials that may limit the translation of the results of these trials into real-world application. We identified 7999 potentially eligible trial participants from a community-based health cohort study and invited them to participate in a randomized controlled trial of an online cognitive behavioural therapy programme for people with depression. We compared those who consented to being assessed for trial inclusion with nonconsenters on demographic, clinical and behavioural indicators captured in the health study. Any potentially biasing factors were then assessed for their association with depression outcome among trial participants to evaluate the existence of sampling bias. Of the 35 health survey variables explored, only 4 were independently associated with higher likelihood of consenting-female sex (odds ratio (OR) 1.11, 95% confidence interval (CI) 1.05-1.19), speaking English at home (OR 1.48, 95% CI 1.15-1.90) higher education (OR 1.67, 95% CI 1.46-1.92) and a prior diagnosis of depression (OR 1.37, 95% CI 1.22-1.55). The multivariate model accounted for limited variance (C-statistic 0.6) in explaining participation. These four factors were not significantly associated with either the primary trial outcome measure or any differential impact by intervention arm. This demonstrates that, among eligible trial participants, few factors were associated with the consent to participate. There was no indication that such self-selection biased the trial results or would limit the generalizability and translation into a public or clinical setting.
International Nuclear Information System (INIS)
Cologne, J.B.; Preston, D.L.
1998-01-01
Biological dosimeters are useful for epidemiologic risk assessment in populations exposed to catastrophic nuclear events and as a means of validating physical dosimetry in radiation workers. Application requires knowledge of the magnitude of uncertainty in the biological dose estimates and an understanding of potential statistical pitfalls arising from their use. This paper describes the statistical aspects of biological dosimetry in general and presents a detailed analysis in the specific case of dosimetry for risk assessment using stable chromosome aberration frequency. Biological dose estimates may be obtained from a dose-response curve, but negative estimates can result and adjustment must be made for regression bias due to imprecise estimation when the estimates are used in regression analyses. Posterior-mean estimates, derived as the mean of the distribution of true doses compatible with a given value of the biological endpoint, have several desirable properties: they are nonnegative, less sensitive to extreme skewness in the true dose distribution, and implicitly adjusted to avoid regression bias. The methods necessitate approximating the true-dose distribution in the population in which biological dosimetry is being applied, which calls for careful consideration of this distribution through other information. An important question addressed here is to what extent the methods are robust to misspecification of this distribution, because in many applications of biological dosimetry it cannot be characterized well. The findings suggest that dosimetry based solely on stable chromosome aberration frequency may be useful for population-based risk assessment
XSDRNPM-S biasing of MORSE-SGC/S shipping-cask calculations
International Nuclear Information System (INIS)
Hoffman, T.J.; Tang, J.S.
1982-06-01
This report describes implementation of a systematic approach for biasing a Monte Carlo radiation transport calculation. In particular, the adjoint fluxes from a one-dimensional discrete ordinates calculation with the XSDRNPM-S code are used to generate biasing parameters for the multigroup Monte Carlo code, MORSE-SGC/S. Application of this biasing procedure to several deep penetration spent fuel shipping cask problems is also reported. The results obtained for neutron and gamma-ray transport indicate that relatively inexpensive Monte Carlo calculations are possible for dry and water filled shipping cask problems using these procedures. 5 tables
On the Limitations of Variational Bias Correction
Moradi, Isaac; Mccarty, Will; Gelaro, Ronald
2018-01-01
Satellite radiances are the largest dataset assimilated into Numerical Weather Prediction (NWP) models, however the data are subject to errors and uncertainties that need to be accounted for before assimilating into the NWP models. Variational bias correction uses the time series of observation minus background to estimate the observations bias. This technique does not distinguish between the background error, forward operator error, and observations error so that all these errors are summed up together and counted as observation error. We identify some sources of observations errors (e.g., antenna emissivity, non-linearity in the calibration, and antenna pattern) and show the limitations of variational bias corrections on estimating these errors.
Cognitive biases and decision making in gambling.
Chóliz, Mariano
2010-08-01
Heuristics and cognitive biases can occur in reasoning and decision making. Some of them are very common in gamblers (illusion of control, representativeness, availability, etc.). Structural characteristics and functioning of games of chance favor the appearance of these biases. Two experiments were conducted with nonpathological gamblers. The first experiment was a game of dice with wagers. In the second experiment, the participants played two bingo games. Specific rules of the games favored the appearance of cognitive bias (illusion of control) and heuristics (representativeness and availability) and influence on the bets. Results and implications for gambling are discussed.
Removing Malmquist bias from linear regressions
Verter, Frances
1993-01-01
Malmquist bias is present in all astronomical surveys where sources are observed above an apparent brightness threshold. Those sources which can be detected at progressively larger distances are progressively more limited to the intrinsically luminous portion of the true distribution. This bias does not distort any of the measurements, but distorts the sample composition. We have developed the first treatment to correct for Malmquist bias in linear regressions of astronomical data. A demonstration of the corrected linear regression that is computed in four steps is presented.
Reducing status quo bias in choice experiments
DEFF Research Database (Denmark)
Bonnichsen, Ole; Ladenburg, Jacob
In stated preference literature, the tendency to choose the alternative representing the status quo situation seems to exceed real life status quo effects. Accordingly, status quo bias can be a problem. In Choice Experiments, status quo bias is found to be strongly correlated with protest attitudes...... toward the cost attribute. If economic values are to be elicited, this problem is difficult to remedy. In a split sample framework we test a novel ex-ante entreaty aimed specifically at the cost attribute and find that it effectively reduces status quo bias and improves the internal validity...
delta-biased Josephson tunnel junctions
DEFF Research Database (Denmark)
Monaco, R.; Mygind, Jesper; Koshelet, V.
2010-01-01
Abstract: The behavior of a long Josephson tunnel junction drastically depends on the distribution of the dc bias current. We investigate the case in which the bias current is fed in the central point of a one-dimensional junction. Such junction configuration has been recently used to detect...... the persistent currents circulating in a superconducting loop. Analytical and numerical results indicate that the presence of fractional vortices leads to remarkable differences from the conventional case of uniformly distributed dc bias current. The theoretical findings are supported by detailed measurements...
Statistics of spatially integrated speckle intensity difference
DEFF Research Database (Denmark)
Hanson, Steen Grüner; Yura, Harold
2009-01-01
We consider the statistics of the spatially integrated speckle intensity difference obtained from two separated finite collecting apertures. For fully developed speckle, closed-form analytic solutions for both the probability density function and the cumulative distribution function are derived...... here for both arbitrary values of the mean number of speckles contained within an aperture and the degree of coherence of the optical field. Additionally, closed-form expressions are obtained for the corresponding nth statistical moments....
Inverse Statistics in the Foreign Exchange Market
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...
Statistical Physics An Introduction
Yoshioka, Daijiro
2007-01-01
This book provides a comprehensive presentation of the basics of statistical physics. The first part explains the essence of statistical physics and how it provides a bridge between microscopic and macroscopic phenomena, allowing one to derive quantities such as entropy. Here the author avoids going into details such as Liouville’s theorem or the ergodic theorem, which are difficult for beginners and unnecessary for the actual application of the statistical mechanics. In the second part, statistical mechanics is applied to various systems which, although they look different, share the same mathematical structure. In this way readers can deepen their understanding of statistical physics. The book also features applications to quantum dynamics, thermodynamics, the Ising model and the statistical dynamics of free spins.
Statistical symmetries in physics
International Nuclear Information System (INIS)
Green, H.S.; Adelaide Univ., SA
1994-01-01
Every law of physics is invariant under some group of transformations and is therefore the expression of some type of symmetry. Symmetries are classified as geometrical, dynamical or statistical. At the most fundamental level, statistical symmetries are expressed in the field theories of the elementary particles. This paper traces some of the developments from the discovery of Bose statistics, one of the two fundamental symmetries of physics. A series of generalizations of Bose statistics is described. A supersymmetric generalization accommodates fermions as well as bosons, and further generalizations, including parastatistics, modular statistics and graded statistics, accommodate particles with properties such as 'colour'. A factorization of elements of ggl(n b ,n f ) can be used to define truncated boson operators. A general construction is given for q-deformed boson operators, and explicit constructions of the same type are given for various 'deformed' algebras. A summary is given of some of the applications and potential applications. 39 refs., 2 figs
The statistical stability phenomenon
Gorban, Igor I
2017-01-01
This monograph investigates violations of statistical stability of physical events, variables, and processes and develops a new physical-mathematical theory taking into consideration such violations – the theory of hyper-random phenomena. There are five parts. The first describes the phenomenon of statistical stability and its features, and develops methods for detecting violations of statistical stability, in particular when data is limited. The second part presents several examples of real processes of different physical nature and demonstrates the violation of statistical stability over broad observation intervals. The third part outlines the mathematical foundations of the theory of hyper-random phenomena, while the fourth develops the foundations of the mathematical analysis of divergent and many-valued functions. The fifth part contains theoretical and experimental studies of statistical laws where there is violation of statistical stability. The monograph should be of particular interest to engineers...
The familiar versus the unfamiliar: Familiarity bias amongst individual investors
Directory of Open Access Journals (Sweden)
Annalien De Vries
2017-02-01
Full Text Available Purpose: The purpose of this study was to investigate the existence of familiarity bias amongst individual investors in the South African stock market. Problem investigated: According to Warren Buffet, one needs to maintain emotional detachment if one wants to be a successful investor. However, recent research indicates that the perceptions of companies’ products and brands may influence individuals’ investment decisions in the stock market. This phenomenon implies that the investment decisions of individual investors are not purely based on firm fundamentals as suggested by traditional finance theories, but might be driven partly by the positive or negative attitude they have towards certain companies’ products and brands. The existence of familiarity bias amongst individual investors was investigated to determine if individuals prefer to invest in companies they are familiar with as opposed to unfamiliar companies. Methodology: A quantitative approach was followed. An online survey was used to show images of familiar and unfamiliar company brands to respondents, whereafter respondents were asked to indicate whether they will invest in the shares of the identified companies. The statistical analysis entailed descriptive statistics as well as one-way analyses of variance to test the stated hypotheses. Main findings: The results of this exploratory study indicate that investors do exhibit familiarity bias when choosing between different companies to invest in. Value of the research: The inclination of individual investors to invest in familiar corporate brands can have implications for the marketing industry, financial markets, the performance of companies as well as the investment performance of individual investors in the sense that it would seem that company brands could have an influence on investment decisions.
Schoenecker, Kathryn A.; Lubow, Bruce C.
2016-01-01
Accurately estimating the size of wildlife populations is critical to wildlife management and conservation of species. Raw counts or “minimum counts” are still used as a basis for wildlife management decisions. Uncorrected raw counts are not only negatively biased due to failure to account for undetected animals, but also provide no estimate of precision on which to judge the utility of counts. We applied a hybrid population estimation technique that combined sightability modeling, radio collar-based mark-resight, and simultaneous double count (double-observer) modeling to estimate the population size of elk in a high elevation desert ecosystem. Combining several models maximizes the strengths of each individual model while minimizing their singular weaknesses. We collected data with aerial helicopter surveys of the elk population in the San Luis Valley and adjacent mountains in Colorado State, USA in 2005 and 2007. We present estimates from 7 alternative analyses: 3 based on different methods for obtaining a raw count and 4 based on different statistical models to correct for sighting probability bias. The most reliable of these approaches is a hybrid double-observer sightability model (model MH), which uses detection patterns of 2 independent observers in a helicopter plus telemetry-based detections of radio collared elk groups. Data were fit to customized mark-resight models with individual sighting covariates. Error estimates were obtained by a bootstrapping procedure. The hybrid method was an improvement over commonly used alternatives, with improved precision compared to sightability modeling and reduced bias compared to double-observer modeling. The resulting population estimate corrected for multiple sources of undercount bias that, if left uncorrected, would have underestimated the true population size by as much as 22.9%. Our comparison of these alternative methods demonstrates how various components of our method contribute to improving the final
Equilibrium statistical mechanics
Jackson, E Atlee
2000-01-01
Ideal as an elementary introduction to equilibrium statistical mechanics, this volume covers both classical and quantum methodology for open and closed systems. Introductory chapters familiarize readers with probability and microscopic models of systems, while additional chapters describe the general derivation of the fundamental statistical mechanics relationships. The final chapter contains 16 sections, each dealing with a different application, ordered according to complexity, from classical through degenerate quantum statistical mechanics. Key features include an elementary introduction t
Applied statistics for economists
Lewis, Margaret
2012-01-01
This book is an undergraduate text that introduces students to commonly-used statistical methods in economics. Using examples based on contemporary economic issues and readily-available data, it not only explains the mechanics of the various methods, it also guides students to connect statistical results to detailed economic interpretations. Because the goal is for students to be able to apply the statistical methods presented, online sources for economic data and directions for performing each task in Excel are also included.
Mineral industry statistics 1975
Energy Technology Data Exchange (ETDEWEB)
1978-01-01
Production, consumption and marketing statistics are given for solid fuels (coal, peat), liquid fuels and gases (oil, natural gas), iron ore, bauxite and other minerals quarried in France, in 1975. Also accident statistics are included. Production statistics are presented of the Overseas Departments and territories (French Guiana, New Caledonia, New Hebrides). An account of modifications in the mining field in 1975 is given. Concessions, exploitation permits, and permits solely for prospecting for mineral products are discussed. (In French)
Lectures on statistical mechanics
Bowler, M G
1982-01-01
Anyone dissatisfied with the almost ritual dullness of many 'standard' texts in statistical mechanics will be grateful for the lucid explanation and generally reassuring tone. Aimed at securing firm foundations for equilibrium statistical mechanics, topics of great subtlety are presented transparently and enthusiastically. Very little mathematical preparation is required beyond elementary calculus and prerequisites in physics are limited to some elementary classical thermodynamics. Suitable as a basis for a first course in statistical mechanics, the book is an ideal supplement to more convent
Directory of Open Access Journals (Sweden)
Mirjam Nielen
2017-01-01
Full Text Available Always wondered why research papers often present rather complicated statistical analyses? Or wondered how to properly analyse the results of a pragmatic trial from your own practice? This talk will give an overview of basic statistical principles and focus on the why of statistics, rather than on the how.This is a podcast of Mirjam's talk at the Veterinary Evidence Today conference, Edinburgh November 2, 2016.
Equilibrium statistical mechanics
Mayer, J E
1968-01-01
The International Encyclopedia of Physical Chemistry and Chemical Physics, Volume 1: Equilibrium Statistical Mechanics covers the fundamental principles and the development of theoretical aspects of equilibrium statistical mechanics. Statistical mechanical is the study of the connection between the macroscopic behavior of bulk matter and the microscopic properties of its constituent atoms and molecules. This book contains eight chapters, and begins with a presentation of the master equation used for the calculation of the fundamental thermodynamic functions. The succeeding chapters highlight t
Mahalanobis, P C
1965-01-01
Contributions to Statistics focuses on the processes, methodologies, and approaches involved in statistics. The book is presented to Professor P. C. Mahalanobis on the occasion of his 70th birthday. The selection first offers information on the recovery of ancillary information and combinatorial properties of partially balanced designs and association schemes. Discussions focus on combinatorial applications of the algebra of association matrices, sample size analogy, association matrices and the algebra of association schemes, and conceptual statistical experiments. The book then examines latt
Biasing anisotropic scattering kernels for deep-penetration Monte Carlo calculations
International Nuclear Information System (INIS)
Carter, L.L.; Hendricks, J.S.
1983-01-01
The exponential transform is often used to improve the efficiency of deep-penetration Monte Carlo calculations. This technique is usually implemented by biasing the distance-to-collision kernel of the transport equation, but leaving the scattering kernel unchanged. Dwivedi obtained significant improvements in efficiency by biasing an isotropic scattering kernel as well as the distance-to-collision kernel. This idea is extended to anisotropic scattering, particularly the highly forward Klein-Nishina scattering of gamma rays
With a 2k-ADC to 4k-spectrometry via two biased amplifiers
Energy Technology Data Exchange (ETDEWEB)
Goerner, W; Kleeberg, H [Zentralinstitut fuer Kernforschung, Rossendorf bei Dresden (German Democratic Republic)
1978-01-12
In order to obtain the double digital spread in high resolution nuclear spectrometry, two biased amplifiers were linked in parallel mode to the 10 V-input of a 2k-ADC. The arrangement works like a hybrid (1 bit scale - 11 bits Wilkinson) converter. A careful adjustment of the two bias levels (approximately 0V and approximately 6V) and the post-amplification (approximately 2) delivered a good linearity of the 4k-spectrum.
Boslaugh, Sarah
2008-01-01
Need to learn statistics as part of your job, or want some help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference that's perfect for anyone with no previous background in the subject. This book gives you a solid understanding of statistics without being too simple, yet without the numbing complexity of most college texts. You get a firm grasp of the fundamentals and a hands-on understanding of how to apply them before moving on to the more advanced material that follows. Each chapter presents you with easy-to-follow descriptions illustrat
Understanding Computational Bayesian Statistics
Bolstad, William M
2011-01-01
A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistic
Annual Statistical Supplement, 2002
Social Security Administration — The Annual Statistical Supplement, 2002 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...