Statistical framework for estimating GNSS bias
Vierinen, Juha; Rideout, William C; Erickson, Philip J; Norberg, Johannes
2015-01-01
We present a statistical framework for estimating global navigation satellite system (GNSS) non-ionospheric differential time delay bias. The biases are estimated by examining differences of measured line integrated electron densities (TEC) that are scaled to equivalent vertical integrated densities. The spatio-temporal variability, instrumentation dependent errors, and errors due to inaccurate ionospheric altitude profile assumptions are modeled as structure functions. These structure functions determine how the TEC differences are weighted in the linear least-squares minimization procedure, which is used to produce the bias estimates. A method for automatic detection and removal of outlier measurements that do not fit into a model of receiver bias is also described. The same statistical framework can be used for a single receiver station, but it also scales to a large global network of receivers. In addition to the Global Positioning System (GPS), the method is also applicable to other dual frequency GNSS s...
Statistical bias in material decomposition in low photon statistics region
Rajbhandary, Paurakh L.; Pelc, Norbert J.
2015-03-01
We show that in material decomposition, statistical bias exists in the low photon regime due to non-linearity including but not limited to the log operation and polychromatic measurements. As new scan methods divide the total number of photons into an increasing number of measurements (e.g., energy bins, projection paths) and as developers seek to reduce radiation dose, the number of photons per measurement will decrease and estimators should be robust against bias at low photon counts. We study bias as a function of total flux and spectral spread, which provides insight when parameters like material thicknesses, number of energy bins, and number of projection views change. We find that the bias increases with lower photon counts, wide spectrum, with more number of energy bins and more projection views. Our simulation, with ideal photon counting detectors, show biases up to 2.4 % in basis material images. We propose a bias correction method in projection space that uses a multi dimensional look up table. With the correction, the relative bias in CT images is within 0.5 ± 0.17%.
Magnification Bias in Gravitational Arc Statistics
Caminha, G B; Makler, M; Mollerach, S; Roulet, E
2013-01-01
The statistics of arcs in galaxy clusters is a powerful probe of the inner parts of cluster structure and may provide complementary cosmological constraints. Although progresses involving simulations at the image level have improved the agreement among modelling and observations of arc abundance, there are still discrepancies regarding the redshift distribution of strong lensing clusters. Besides, fast "semi-analytic" methods still have to incorporate the success obtained with simulations. In this paper we discuss the contribution of magnification in gravitational arc statistics. Although lensing conserves surface brightness, the magnification (\\mu) increases the signal-to-noise ratio of the arcs in the images, enhancing their detectability. We present an approach to include this and other observational effects in semi-analytic calculations for arc statistics. The cross section for arc formation (\\sigma) is computed through a semi-analytic method based on the eigenvalue ratio of the magnification tensor. Usin...
Parametric study of statistical bias in laser Doppler velocimetry
International Nuclear Information System (INIS)
Analytical studies have often assumed that LDV velocity bias depends on turbulence intensity in conjunction with one or more characteristic time scales, such as the time between validated signals, the time between data samples, and the integral turbulence time-scale. These parameters are presently varied independently, in an effort to quantify the biasing effect. Neither of the post facto correction methods employed is entirely accurate. The mean velocity bias error is found to be nearly independent of data validation rate. 15 refs
Beyond Kaiser bias: mildly non-linear two-point statistics of densities in distant spheres
Uhlemann, C.; Codis, S; Kim, J.; Pichon, C.; Bernardeau, F.; Pogosyan, D; Park, C.; L'Huillier, B.
2016-01-01
Simple parameter-free analytic bias functions for the two-point correlation of densities in spheres at large separation are presented. These bias functions generalize the so-called Kaiser bias to the mildly non-linear regime for arbitrary density contrasts. The derivation is carried out in the context of large deviation statistics while relying on the spherical collapse model. A logarithmic transformation provides a saddle approximation which is valid for the whole range of densities and show...
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.
Improving uncertainty estimation in urban hydrological modeling by statistically describing bias
Directory of Open Access Journals (Sweden)
D. Del Giudice
2013-10-01
Full Text Available Hydrodynamic models are useful tools for urban water management. Unfortunately, it is still challenging to obtain accurate results and plausible uncertainty estimates when using these models. In particular, with the currently applied statistical techniques, flow predictions are usually overconfident and biased. In this study, we present a flexible and relatively efficient methodology (i to obtain more reliable hydrological simulations in terms of coverage of validation data by the uncertainty bands and (ii to separate prediction uncertainty into its components. Our approach acknowledges that urban drainage predictions are biased. This is mostly due to input errors and structural deficits of the model. We address this issue by describing model bias in a Bayesian framework. The bias becomes an autoregressive term additional to white measurement noise, the only error type accounted for in traditional uncertainty analysis. To allow for bigger discrepancies during wet weather, we make the variance of bias dependent on the input (rainfall or/and output (runoff of the system. Specifically, we present a structured approach to select, among five variants, the optimal bias description for a given urban or natural case study. We tested the methodology in a small monitored stormwater system described with a parsimonious model. Our results clearly show that flow simulations are much more reliable when bias is accounted for than when it is neglected. Furthermore, our probabilistic predictions can discriminate between three uncertainty contributions: parametric uncertainty, bias, and measurement errors. In our case study, the best performing bias description is the output-dependent bias using a log-sinh transformation of data and model results. The limitations of the framework presented are some ambiguity due to the subjective choice of priors for bias parameters and its inability to address the causes of model discrepancies. Further research should focus on
Improving uncertainty estimation in urban hydrological modeling by statistically describing bias
Directory of Open Access Journals (Sweden)
D. Del Giudice
2013-04-01
Full Text Available Hydrodynamic models are useful tools for urban water management. Unfortunately, it is still challenging to obtain accurate results and plausible uncertainty estimates when using these models. In particular, with the currently applied statistical techniques, flow predictions are usually overconfident and biased. In this study, we present a flexible and computationally efficient methodology (i to obtain more reliable hydrological simulations in terms of coverage of validation data by the uncertainty bands and (ii to separate prediction uncertainty into its components. Our approach acknowledges that urban drainage predictions are biased. This is mostly due to input errors and structural deficits of the model. We address this issue by describing model bias in a Bayesian framework. The bias becomes an autoregressive term additional to white measurement noise, the only error type accounted for in traditional uncertainty analysis in urban hydrology. To allow for bigger discrepancies during wet weather, we make the variance of bias dependent on the input (rainfall or/and output (runoff of the system. Specifically, we present a structured approach to select, among five variants, the optimal bias description for a given urban or natural case study. We tested the methodology in a small monitored stormwater system described by means of a parsimonious model. Our results clearly show that flow simulations are much more reliable when bias is accounted for than when it is neglected. Furthermore, our probabilistic predictions can discriminate between three uncertainty contributions: parametric uncertainty, bias (due to input and structural errors, and measurement errors. In our case study, the best performing bias description was the output-dependent bias using a log-sinh transformation of data and model results. The limitations of the framework presented are some ambiguity due to the subjective choice of priors for bias parameters and its inability to directly
Beyond Kaiser bias: mildly non-linear two-point statistics of densities in distant spheres
Uhlemann, C; Kim, J; Pichon, C; Bernardeau, F; Pogosyan, D; Park, C; L'Huillier, B
2016-01-01
Simple parameter-free analytic bias functions for the two-point correlation of densities in spheres at large separation are presented. These bias functions generalize the so-called Kaiser bias to the mildly non-linear regime for arbitrary density contrasts. The derivation is carried out in the context of large deviation statistics while relying on the spherical collapse model. A logarithmic transformation provides a saddle approximation which is valid for the whole range of densities and shown to be accurate against the 30 Gpc cube state-of-the-art Horizon Run 4 simulation. Special configurations of two concentric spheres that allow to identify peaks are employed to obtain the conditional bias and a proxy to BBKS extrema correlation functions. These analytic bias functions should be used jointly with extended perturbation theory to predict two-point clustering statistics as they capture the non-linear regime of structure formation at the percent level down to scales of about 10 Mpc/h at redshift 0. Conversely...
Bias Expansion of Spatial Statistics and Approximation of Differenced Lattice Point Counts
Indian Academy of Sciences (India)
Daniel J Nordman; Soumendra N Lahiri
2011-05-01
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. In particular, such bias expansions often require approximating a difference between two lattice point counts, where the counts correspond to a set of increasing domain (i.e., the sampling region) and an intersection of this set with a vector translate of itself. Non-trivially, the approximation error needs to be of smaller order than the spatial region’s perimeter length. For all convex regions in 2-dimensional Euclidean space and certain unions of convex sets, we show that a difference in areas can approximate a difference in lattice point counts to this required accuracy, even though area can poorly measure the lattice point count of any single set involved in the difference. When investigating large-sample properties of spatial estimators, this approximation result facilitates direct calculation of limiting bias, because, unlike counts, differences in areas are often tractable to compute even with non-rectangular regions. We illustrate the counting approximations with two statistical examples.
Ray, Robert L
2016-01-01
Two-particle correlation measurements and analysis are an important component of the relativistic heavy-ion physics program. In particular, particle pair-number correlations on two-dimensional transverse momentum ($p_t$) allow unique access to soft, semi-hard and hard-scattering processes in these collisions. Precise measurements of this type of correlation are essential for understanding the dynamics in heavy-ion collisions. However, transverse momentum correlation measurements are especially vulnerable to statistical and systematic biases. In this paper the origins of these large bias effects are explained and mathematical correlation forms are derived from mean-$p_t$ fluctuation quantities in the literature in an effort to minimize bias. Monte Carlo simulations are then used to test the degree to which each correlation definition leads to unbiased results in realistic applications. Several correlation forms are shown to be unacceptable for data analysis applications while several others are shown to reprod...
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.
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.
Um, Myoung-Jin; Kim, Hanbeen; Heo, Jun-Haeng
2016-08-01
A general circulation model (GCM) can be applied to project future climate factors, such as precipitation and atmospheric temperature, to study hydrological and environmental climate change. Although many improvements in GCMs have been proposed recently, projected climate data are still required to be corrected for the biases in generating data before applying the model to practical applications. In this study, a new hybrid process was proposed, and its ability to perform bias correction for the prediction of annual precipitation and annual daily maxima, was tested. The hybrid process in this study was based on quantile mapping with the gamma and generalized extreme value (GEV) distributions and a spline technique to correct the bias of projected daily precipitation. The observed and projected daily precipitation values from the selected stations were analyzed using three bias correction methods, namely, linear scaling, quantile mapping, and hybrid methods. The performances of these methods were analyzed to find the optimal method for prediction of annual precipitation and annual daily maxima. The linear scaling method yielded the best results for estimating the annual average precipitation, while the hybrid method was optimal for predicting the variation in annual precipitation. The hybrid method described the statistical characteristics of the annual maximum series (AMS) similarly to the observed data. In addition, this method demonstrated the lowest root mean squared error (RMSE) and the highest coefficient of determination (R2) for predicting the quantiles of the AMS for the extreme value analysis of precipitation.
Statistical Bias Correction scheme for climate change impact assessment at a basin scale
Nyunt, C. T.
2013-12-01
Global climate models (GCMs) are the primary tool for understanding how the global climate may change in the future. GCM precipitation is characterized by underestimation of heavy precipitation, frequency errors by low intensity with long drizzle rain days and fail to catch the inter-seasonal change compared to the ground data. This study focus on the basin scale climate change impact study and we proposed the method for the multi model (GCMs) selection method together with the statistical bias correction method which cover the major deficiencies of GCM biases for climate change impact study at the basin level. The proposed method had been tested its applicability in the various river basin under different climate such as semiarid region in Tunisia, tropical monsoonal climate in Philippines and temperate humid region in Japan. It performed well enough for the climate change impact study in the basin scale and it can catch the point scale and basin scale climatology precipitation very well during the historical simulation. We found the GCM simulation during baiu season dissipate the baiu activity more earlier than the actual one when compared to the in-situ station data in Japan. For that case, the proposed bias correction performed in each season to reduce the bias of GCM for the impact study. The proposed bias correction method is still tested in different river basin in the world to check it applicability and now under developing as the web interface as the handy and efficient tool for the end users from the different parts of the world.
Bliefernicht, Jan; Laux, Patrick; Siegmund, Jonatan; Kunstmann, Harald
2013-04-01
The development and application of statistical techniques with a special focus on a recalibration of meteorological or hydrological forecasts to eliminate the bias between forecasts and observations has received a great deal of attention in recent years. One reason is that retrospective forecasts are nowadays available which allows for a proper training and validation of this kind of techniques. The objective of this presentation is to propose several statistical techniques with different degree of complexity and to evaluate and compare their performance for a recalibration of seasonal ensemble forecasts of monthly precipitation. The techniques selected in this study range from straightforward normal score and quantile-quantile transformation, local scaling, to more sophisticated and novel statistical techniques such as Copula-based methodology recently proposed by Laux et al. (2011). The seasonal forecasts are derived from the Climate Forecast System Version 2. This version is the current coupled ocean-atmosphere general circulation model of the U.S. National Centers for Environmental Prediction used to provide forecasts up to nine months. The CFS precipitation forecasts are compared to monthly precipitation observations from the Global Precipitation Climatology Centre. The statistical techniques are tested for semi-arid regions in West Africa and the Indian subcontinent focusing on large-scale river basins such as the Ganges and the Volta basin. In both regions seasonal precipitation forecasts are a crucial source of information for the prediction of hydro-meteorological extremes, in particular for droughts. The evaluation is done using retrospective CFS ensemble forecast from 1982 to 2009. The training of the statistical techniques is done in a cross-validation mode. The outcome of this investigation illustrates large systematic differences between forecasts and observations, in particular for the Volta basin in West Africa. The selection of straightforward
Greenberg, Ariela Caren
Differential item functioning (DIF) and differential distractor functioning (DDF) are methods used to screen for item bias (Camilli & Shepard, 1994; Penfield, 2008). Using an applied empirical example, this mixed-methods study examined the congruency and relationship of DIF and DDF methods in screening multiple-choice items. Data for Study I were drawn from item responses of 271 female and 236 male low-income children on a preschool science assessment. Item analyses employed a common statistical approach of the Mantel-Haenszel log-odds ratio (MH-LOR) to detect DIF in dichotomously scored items (Holland & Thayer, 1988), and extended the approach to identify DDF (Penfield, 2008). Findings demonstrated that the using MH-LOR to detect DIF and DDF supported the theoretical relationship that the magnitude and form of DIF and are dependent on the DDF effects, and demonstrated the advantages of studying DIF and DDF in multiple-choice items. A total of 4 items with DIF and DDF and 5 items with only DDF were detected. Study II incorporated an item content review, an important but often overlooked and under-published step of DIF and DDF studies (Camilli & Shepard). Interviews with 25 female and 22 male low-income preschool children and an expert review helped to interpret the DIF and DDF results and their comparison, and determined that a content review process of studied items can reveal reasons for potential item bias that are often congruent with the statistical results. Patterns emerged and are discussed in detail. The quantitative and qualitative analyses were conducted in an applied framework of examining the validity of the preschool science assessment scores for evaluating science programs serving low-income children, however, the techniques can be generalized for use with measures across various disciplines of research.
Directory of Open Access Journals (Sweden)
N. S. Vithlani
2016-08-01
Full Text Available For the future projections Global climate models (GCMs enable development of climate projections and relate greenhouse gas forcing to future potential climate states. When focusing it on smaller scales it exhibit some limitations to overcome this problem, regional climate models (RCMs and other downscaling methods have been developed. To ensure statistics of the downscaled output matched the corresponding statistics of the observed data, bias correction was used. Quantify future changes of climate extremes were analyzed, based on these downscaled data from two RCMs grid points. Subset of indices and models, results of bias corrected model output and raw for the present day climate were compared with observation, which demonstrated that bias correction is important for RCM outputs. Bias correction directed agreements of extreme climate indices for future climate it does not correct for lag inverse autocorrelation and fraction of wet and dry days. But, it was observed that adjusting both the biases in the mean and variability, relatively simple non-linear correction, leads to better reproduction of observed extreme daily and multi-daily precipitation amounts. Due to climate change temperature and precipitation will increased day by day.
A statistical characterization of the Galileo-to-GPS inter-system bias
Gioia, Ciro; Borio, Daniele
2016-06-01
Global navigation satellite system operates using independent time scales and thus inter-system time offsets have to be determined to enable multi-constellation navigation solutions. GPS/Galileo inter-system bias and drift are evaluated here using different types of receivers: two mass market and two professional receivers. Moreover, three different approaches are considered for the inter-system bias determination: in the first one, the broadcast Galileo to GPS time offset is used to align GPS and Galileo time scales. In the second, the inter-system bias is included in the multi-constellation navigation solution and is estimated using the measurements available. Finally, an enhanced algorithm using constraints on the inter-system bias time evolution is proposed. The inter-system bias estimates obtained with the different approaches are analysed and their stability is experimentally evaluated using the Allan deviation. The impact of the inter-system bias on the position velocity time solution is also considered and the performance of the approaches analysed is evaluated in terms of standard deviation and mean errors for both horizontal and vertical components. From the experiments, it emerges that the inter-system bias is very stable and that the use of constraints, modelling the GPS/Galileo inter-system bias behaviour, significantly improves the performance of multi-constellation navigation.
A statistical characterization of the Galileo-to-GPS inter-system bias
Gioia, Ciro; Borio, Daniele
2016-11-01
Global navigation satellite system operates using independent time scales and thus inter-system time offsets have to be determined to enable multi-constellation navigation solutions. GPS/Galileo inter-system bias and drift are evaluated here using different types of receivers: two mass market and two professional receivers. Moreover, three different approaches are considered for the inter-system bias determination: in the first one, the broadcast Galileo to GPS time offset is used to align GPS and Galileo time scales. In the second, the inter-system bias is included in the multi-constellation navigation solution and is estimated using the measurements available. Finally, an enhanced algorithm using constraints on the inter-system bias time evolution is proposed. The inter-system bias estimates obtained with the different approaches are analysed and their stability is experimentally evaluated using the Allan deviation. The impact of the inter-system bias on the position velocity time solution is also considered and the performance of the approaches analysed is evaluated in terms of standard deviation and mean errors for both horizontal and vertical components. From the experiments, it emerges that the inter-system bias is very stable and that the use of constraints, modelling the GPS/Galileo inter-system bias behaviour, significantly improves the performance of multi-constellation navigation.
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
Zhang Zhang; Li Jun; Cui Peng; Ding Feng; Li Ang; Townsend Jeffrey P; Yu Jun
2012-01-01
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...
How cognitive biases can distort environmental statistics: introducing the rough estimation task.
Wilcockson, Thomas D W; Pothos, Emmanuel M
2016-04-01
The purpose of this study was to develop a novel behavioural method to explore cognitive biases. The task, called the Rough Estimation Task, simply involves presenting participants with a list of words that can be in one of three categories: appetitive words (e.g. alcohol, food, etc.), neutral related words (e.g. musical instruments) and neutral unrelated words. Participants read the words and are then asked to state estimates for the percentage of words in each category. Individual differences in the propensity to overestimate the proportion of appetitive stimuli (alcohol-related or food-related words) in a word list were associated with behavioural measures (i.e. alcohol consumption, hazardous drinking, BMI, external eating and restrained eating, respectively), thereby providing evidence for the validity of the task. The task was also found to be associated with an eye-tracking attentional bias measure. The Rough Estimation Task is motivated in relation to intuitions with regard to both the behaviour of interest and the theory of cognitive biases in substance use.
Not a Copernican observer: biased peculiar velocity statistics in the local Universe
Hellwing, Wojciech A; Feix, Martin; Bilicki, Maciej
2016-01-01
We assess the effect of the local large scale structure on the estimation of two-point statistics of the observed radial peculiar velocities of galaxies. A large N-body simulation is used to examine these statistics from the perspective of random observers as well as "Local Group (LG)-like" observers conditioned to reside in an environment resembling the observed universe within 20 Mpc. The local environment systematically distorts the shape and amplitude of velocity statistics with respect to ensemble-averaged measurements made by a Copernican (random) observer. The Virgo cluster has the most significant impact, introducing large systematic deviations in all the statistics. For a simple "top-hat" selection function, an idealized survey extending to $\\sim 160h^{-1}\\,{\\rm Mpc}$ or deeper is needed to completely mitigate the effects of the local environment. Using shallower catalogues leads to systematic deviations of the order of $50$ to $200\\%$ depending on the scale considered. For a flat redshift distributi...
International Nuclear Information System (INIS)
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
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). PMID:27471481
Kuusela, Mikael
2015-01-01
We consider the high energy physics unfolding problem where the goal is to estimate the spectrum of elementary particles given observations distorted by the limited resolution of a particle detector. This important statistical inverse problem arising in data analysis at the Large Hadron Collider at CERN consists in estimating the intensity function of an indirectly observed Poisson point process. Unfolding typically proceeds in two steps: one first produces a regularized point estimate of the unknown intensity and then uses the variability of this estimator to form frequentist confidence intervals that quantify the uncertainty of the solution. In this paper, we propose forming the point estimate using empirical Bayes estimation which enables a data-driven choice of the regularization strength through marginal maximum likelihood estimation. Observing that neither Bayesian credible intervals nor standard bootstrap confidence intervals succeed in achieving good frequentist coverage in this problem due to the inh...
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.
Li, R.; Wang, S.-Y.; Gillies, R. R.
2016-04-01
Large biases associated with climate projections are problematic when it comes to their regional application in the assessment of water resources and ecosystems. Here, we demonstrate a method that can reduce systematic biases in regional climate projections. The global and regional climate models employed to demonstrate the technique are the Community Climate System Model (CCSM) and the Weather Research and Forecasting (WRF) model. The method first utilized a statistical regression technique and a global reanalysis dataset to correct biases in the CCSM-simulated variables (e.g., temperature, geopotential height, specific humidity, and winds) that are subsequently used to drive the WRF model. The WRF simulations were conducted for the western United States and were driven with (a) global reanalysis, (b) original CCSM, and (c) bias-corrected CCSM data. The bias-corrected CCSM data led to a more realistic regional climate simulation of precipitation and associated atmospheric dynamics, as well as snow water equivalent (SWE), in comparison to the original CCSM-driven WRF simulation. Since most climate applications rely on existing global model output as the forcing data (i.e., they cannot re-run or change the global model), which often contain large biases, this method provides an effective and economical tool to reduce biases in regional climate downscaling simulations of water resource variables.
Indian Academy of Sciences (India)
V R Durai; Rashmi Bhardwaj
2014-07-01
The output from Global Forecasting System (GFS) T574L64 operational at India Meteorological Department (IMD), New Delhi is used for obtaining location specific quantitative forecast of maximum and minimum temperatures over India in the medium range time scale. In this study, a statistical bias correction algorithm has been introduced to reduce the systematic bias in the 24–120 hour GFS model location specific forecast of maximum and minimum temperatures for 98 selected synoptic stations, representing different geographical regions of India. The statistical bias correction algorithm used for minimizing the bias of the next forecast is Decaying Weighted Mean (DWM), as it is suitable for small samples. The main objective of this study is to evaluate the skill of Direct Model Output (DMO) and Bias Corrected (BC) GFS for location specific forecast of maximum and minimum temperatures over India. The performance skill of 24–120 hour DMO and BC forecast of GFS model is evaluated for all the 98 synoptic stations during summer (May–August 2012) and winter (November 2012–February 2013) seasons using different statistical evaluation skill measures. The magnitude of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) for BC GFS forecast is lower than DMO during both summer and winter seasons. The BC GFS forecasts have higher skill score as compared to GFS DMO over most of the stations in all day-1 to day-5 forecasts during both summer and winter seasons. It is concluded from the study that the skill of GFS statistical BC forecast improves over the GFS DMO remarkably and hence can be used as an operational weather forecasting system for location specific forecast over India.
Casanueva, A.; Kotlarski, S.; Herrera, S.; Fernández, J.; Gutiérrez, J. M.; Boberg, F.; Colette, A.; Christensen, O. B.; Goergen, K.; Jacob, D.; Keuler, K.; Nikulin, G.; Teichmann, C.; Vautard, R.
2016-08-01
Daily precipitation statistics as simulated by the ERA-Interim-driven EURO-CORDEX regional climate model (RCM) ensemble are evaluated over two distinct regions of the European continent, namely the European Alps and Spain. The potential added value of the high-resolution 12 km experiments with respect to their 50 km resolution counterparts is investigated. The statistics considered consist of wet-day intensity and precipitation frequency as a measure of mean precipitation, and three precipitation-derived indicators (90th percentile on wet days—90pWET, contribution of the very wet days to total precipitation—R95pTOT and number of consecutive dry days—CDD). As reference for model evaluation high resolution gridded observational data over continental Spain (Spain011/044) and the Alpine region (EURO4M-APGD) are used. The assessment and comparison of the two resolutions is accomplished not only on their original horizontal grids (approximately 12 and 50 km), but the high-resolution RCMs are additionally regridded onto the coarse 50 km grid by grid cell aggregation for the direct comparison with the low resolution simulations. The direct application of RCMs e.g. in many impact modelling studies is hampered by model biases. Therefore bias correction (BC) techniques are needed at both resolutions to ensure a better agreement between models and observations. In this work, the added value of the high resolution (before and after the bias correction) is assessed and the suitability of these BC methods is also discussed. Three basic BC methods are applied to isolate the effect of biases in mean precipitation, wet-day intensity and wet-day frequency on the derived indicators. Daily precipitation percentiles are strongly affected by biases in the wet-day intensity, whereas the dry spells are better represented when the simulated precipitation frequency is adjusted to the observed one. This confirms that there is no single optimal way to correct for RCM biases, since
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
DEFF Research Database (Denmark)
Thorson, James T.; Kristensen, Kasper
2016-01-01
-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...
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.
Rosenbaum, Paul R
2016-03-01
A common practice with ordered doses of treatment and ordered responses, perhaps recorded in a contingency table with ordered rows and columns, is to cut or remove a cross from the table, leaving the outer corners-that is, the high-versus-low dose, high-versus-low response corners-and from these corners to compute a risk or odds ratio. This little remarked but common practice seems to be motivated by the oldest and most familiar method of sensitivity analysis in observational studies, proposed by Cornfield et al. (1959), which says that to explain a population risk ratio purely as bias from an unobserved binary covariate, the prevalence ratio of the covariate must exceed the risk ratio. Quite often, the largest risk ratio, hence the one least sensitive to bias by this standard, is derived from the corners of the ordered table with the central cross removed. Obviously, the corners use only a portion of the data, so a focus on the corners has consequences for the standard error as well as for bias, but sampling variability was not a consideration in this early and familiar form of sensitivity analysis, where point estimates replaced population parameters. Here, this cross-cut analysis is examined with the aid of design sensitivity and the power of a sensitivity analysis. PMID:26295693
Elvarsson, B. P.; Taylor, L.; Trenkel, Verena; Kupca, V.; Stefansson, G.
2014-01-01
Statistical models of marine ecosystems use a variety of data sources to estimate parameters using composite or weighted likelihood functions with associated weighting issues and questions on how to obtain variance estimates. Regardless of the method used to obtain point estimates, a method is required for variance estimation. A bootstrap technique is introduced for the evaluation of uncertainty in such models, taking into account inherent spatial and temporal correlations in the datasets, wh...
Directory of Open Access Journals (Sweden)
Phillips Carl V
2004-08-01
Full Text Available Abstract Background Publication bias, as typically defined, refers to the decreased likelihood of studies' results being published when they are near the null, not statistically significant, or otherwise "less interesting." But choices about how to analyze the data and which results to report create a publication bias within the published results, a bias I label "publication bias in situ" (PBIS. Discussion PBIS may create much greater bias in the literature than traditionally defined publication bias (the failure to publish any result from a study. The causes of PBIS are well known, consisting of various decisions about reporting that are influenced by the data. But its impact is not generally appreciated, and very little attention is devoted to it. What attention there is consists largely of rules for statistical analysis that are impractical and do not actually reduce the bias in reported estimates. PBIS cannot be reduced by statistical tools because it is not fundamentally a problem of statistics, but rather of non-statistical choices and plain language interpretations. PBIS should be recognized as a phenomenon worthy of study – it is extremely common and probably has a huge impact on results reported in the literature – and there should be greater systematic efforts to identify and reduce it. The paper presents examples, including results of a recent HIV vaccine trial, that show how easily PBIS can have a large impact on reported results, as well as how there can be no simple answer to it. Summary PBIS is a major problem, worthy of substantially more attention than it receives. There are ways to reduce the bias, but they are very seldom employed because they are largely unrecognized.
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.)
Theoretical investigation of exchange bias
Institute of Scientific and Technical Information of China (English)
Xiong Zhi-Jie; Wang Huai-Yu; Ding Ze-Jun
2007-01-01
The exchange bias of bilayer magnetic films consisting of ferromagnetic (FM) and antiferromagnetic (AFM) layers in an uncompensated case is studied by use of the many-body Green's function method of quantum statistical theory.The effects of the layer thickness and temperature and the interfacial coupling strength on the exchange bias HE are investigated. The dependence of the exchange bias HE on the FM layer thickness and temperature is qualitatively in agreement with experimental results. When temperature varies, both the coercivity HC and HE decrease with the temperature increasing. For each FM thickness, there exists a least AFM thickness in which the exchange bias occurs,which is called pinning thickness.
Edelstein, Stuart J; Changeux, Jean-Pierre
2016-09-01
G-protein-coupled receptors (GPCRs) constitute a large group of integral membrane proteins that transduce extracellular signals from a wide range of agonists into targeted intracellular responses. Although the responses can vary depending on the category of G-proteins activated by a particular receptor, responses were also found to be triggered by interactions of the receptor with β-arrestins. It was subsequently discovered that for the same receptor molecule (e.g., the β-adrenergic receptor), some agonists have a propensity to specifically favor responses by G-proteins, others by β-arrestins, as has now been extensively studied. This feature of the GPCR system is known as biased agonism and is subject to various interpretations, including agonist-induced conformational change versus selective stabilization of preexisting active conformations. Here, we explore a complete allosteric framework for biased agonism based on alternative preexisting conformations that bind more strongly, but nonexclusively, either G-proteins or β-arrestins. The framework incorporates reciprocal effects among all interacting molecules. As a result, G-proteins and β-arrestins are in steric competition for binding to the cytoplasmic surface of either the G-protein-favoring or β-arrestin-favoring GPCR conformation. Moreover, through linkage relations, the strength of the interactions of G-proteins or β-arrestins with the corresponding active conformation potentiates the apparent affinity for the agonist, effectively equating these two proteins to allosteric modulators. The balance between response alternatives can also be influenced by the physiological concentrations of either G-proteins or β-arrestins, as well as by phosphorylation or interactions with positive or negative allosteric modulators. The nature of the interactions in the simulations presented suggests novel experimental tests to distinguish more fully among alternative mechanisms. PMID:27602718
Venema, Victor; Lindau, Ralf
2016-04-01
In an accompanying talk we show that well-homogenized national dataset warm more than temperatures from global collections averaged over the region of common coverage. In this poster we want to present auxiliary work about possible biases in the raw observations and on how well relative statistical homogenization can remove trend biases. There are several possible causes of cooling biases, which have not been studied much. Siting could be an important factor. Urban stations tend to move away from the centre to better locations. Many stations started inside of urban areas and are nowadays more outside. Even for villages the temperature difference between the centre and edge can be 0.5°C. When a city station moves to an airport, which often happened around WWII, this takes the station (largely) out of the urban heat island. During the 20th century the Stevenson screen was established as the dominant thermometer screen. This screen protected the thermometer much better against radiation than earlier designs. Deficits of earlier measurement methods have artificially warmed the temperatures in the 19th century. Newer studies suggest we may have underestimated the size of this bias. Currently we are in a transition to Automatic Weather Stations. The net global effect of this transition is not clear at this moment. Irrigation on average decreases the 2m-temperature by about 1 degree centigrade. At the same time, irrigation has increased significantly during the last century. People preferentially live in irrigated areas and weather stations serve agriculture. Thus it is possible that there is a higher likelihood that weather stations are erected in irrigated areas than elsewhere. In this case irrigation could lead to a spurious cooling trend. In the Parallel Observations Science Team of the International Surface Temperature Initiative (ISTI-POST) we are studying influence of the introduction of Stevenson screens and Automatic Weather Stations using parallel measurements
Climate model bias correction and the role of timescales
Directory of Open Access Journals (Sweden)
J. O. Haerter
2010-10-01
Full Text Available It is well known that output from climate models cannot be used to force hydrological simulations without some form of preprocessing to remove the existing biases. In principle, statistical bias correction methodologies act on model output so the statistical properties of the corrected data match those of the observations. However the improvements to the statistical properties of the data are limited to the specific time scale of the fluctuations that are considered. For example, a statistical bias correction methodology for mean daily values might be detrimental to monthly statistics. Also, in applying bias corrections derived from present day to scenario simulations, an assumption is made of persistence of the bias over the largest timescales. We examine the effects of mixing fluctuations on different time scales and suggest an improved statistical methodology, referred to here as a cascade bias correction method, that eliminates, or greatly reduces, the negative effects.
Challenges in bias correcting climate change simulations
Maraun, Douglas; Shepherd, Ted; Zappa, Giuseppe; Gutierrez, Jose; Widmann, Martin; Hagemann, Stefan; Richter, Ingo; Soares, Pedro; Mearns, Linda
2016-04-01
Biases in climate model simulations - if these are directly used as input for impact models - will introduce further biases in subsequent impact simulations. In response to this issue, so-called bias correction methods have been developed to post-process climate model output. These methods are now widely used and a crucial component in the generation of high resolution climate change projections. Bias correction is conceptually similar to model output statistics, which has been successfully used for several decades in numerical weather prediction. Yet in climate science, some authors outrightly dismiss any form of bias correction. Starting from this seeming contradiction, we highlight differences between the two contexts and infer consequences and limitations for the applicability of bias correction to climate change projections. We first show that cross validation approaches successfully used to evaluate weather forecasts are fundamentally insufficient to evaluate climate change bias correction. We further demonstrate that different types of model mismatches with observations require different solutions, and some may not sensibly be mitigated. In particular we consider the influence of large-scale circulation biases, biases in the persistence of weather regimes, and regional biases caused by an insufficient representation of the flow-topography interaction. We conclude with a list of recommendations and suggestions for future research to reduce, to post-process, and to cope with climate model biases.
Pope, Devin G.; Price, Joseph; Wolfers, Justin
2014-01-01
Can raising awareness of racial bias subsequently reduce that bias? We address this question by exploiting the widespread media attention highlighting racial bias among professional basketball referees that occurred in May 2007 following the release of an academic study. Using new data, we confirm that racial bias persisted in the years after the study's original sample, but prior to the media coverage. Subsequent to the media coverage though, the bias completely disappeared. We examine poten...
Bias and variance in continuous EDA
Teytaud, Fabien; Teytaud, Olivier
2009-01-01
Estimation of Distribution Algorithms are based on statistical estimates. We show that when combining classical tools from statistics, namely bias/variance decomposition, reweighting and quasi-randomization, we can strongly improve the convergence rate. All modiﬁcations are easy, compliant with most algorithms, and experimentally very eﬃcient in particular in the parallel case (large oﬀsprings).
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 choic
... Data Consumer Opinion Surveys Home / Research & Statistics Injury Statistics This is the statistic reports page for scientific ... Home Appliances, Maintenance and Construction Injury Statistics Injury Statistics September 30, 2012 Submersions Related to Non-Pool ...
Publication Bias The "File-Drawer Problem" in Scientific Inference
Scargle, J D
1999-01-01
Publication bias arises whenever the probability that a study is published depends on the statistical significance of its results. This bias, often called the file-drawer effect since the unpublished results are imagined to be tucked away in researchers' file cabinets, is potentially a severe impediment to combining the statistical results of studies collected from the literature. With almost any reasonable quantitative model for publication bias, only a small number of studies lost in the file-drawer will produce a significant bias. This result contradicts the well known Fail Safe File Drawer (FSFD) method for setting limits on the potential harm of publication bias, widely used in social, medical and psychic research. This method incorrectly treats the file drawer as unbiased, and almost always misestimates the seriousness of publication bias. A large body of not only psychic research, but medical and social science studies, has mistakenly relied on this method to validate claimed discoveries. Statistical c...
Recursive bias estimation and L2 boosting
Energy Technology Data Exchange (ETDEWEB)
Hengartner, Nicolas W [Los Alamos National Laboratory; Cornillon, Pierre - Andre [INRA, FRANCE; Matzner - Lober, Eric [RENNE, FRANCE
2009-01-01
This paper presents a general iterative bias correction procedure for regression smoothers. This bias reduction schema is shown to correspond operationally to the L{sub 2} Boosting algorithm and provides a new statistical interpretation for L{sub 2} Boosting. We analyze the behavior of the Boosting algorithm applied to common smoothers S which we show depend on the spectrum of I - S. We present examples of common smoother for which Boosting generates a divergent sequence. The statistical interpretation suggest combining algorithm with an appropriate stopping rule for the iterative procedure. Finally we illustrate the practical finite sample performances of the iterative smoother via a simulation study.
Germano, Fabrizio
2008-01-01
Within the spokes model of Chen and Riordan (2007) that allows for non-localized competition among arbitrary numbers of media outlets, we quantify the effect of concentration of ownership on quality and bias of media content. A main result shows that too few commercial outlets, or better, too few separate owners of commercial outlets can lead to substantial bias in equilibrium. Increasing the number of outlets (commercial and non-commercial) tends to bring down this bias; but the strong...
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...... 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....
Interpretation biases in paranoia.
Savulich, George; Freeman, Daniel; Shergill, Sukhi; Yiend, Jenny
2015-01-01
Information in the environment is frequently ambiguous in meaning. Emotional ambiguity, such as the stare of a stranger, or the scream of a child, encompasses possible good or bad emotional consequences. Those with elevated vulnerability to affective disorders tend to interpret such material more negatively than those without, a phenomenon known as "negative interpretation bias." In this study we examined the relationship between vulnerability to psychosis, measured by trait paranoia, and interpretation bias. One set of material permitted broadly positive/negative (valenced) interpretations, while another allowed more or less paranoid interpretations, allowing us to also investigate the content specificity of interpretation biases associated with paranoia. Regression analyses (n=70) revealed that trait paranoia, trait anxiety, and cognitive inflexibility predicted paranoid interpretation bias, whereas trait anxiety and cognitive inflexibility predicted negative interpretation bias. In a group comparison those with high levels of trait paranoia were negatively biased in their interpretations of ambiguous information relative to those with low trait paranoia, and this effect was most pronounced for material directly related to paranoid concerns. Together these data suggest that a negative interpretation bias occurs in those with elevated vulnerability to paranoia, and that this bias may be strongest for material matching paranoid beliefs. We conclude that content-specific biases may be important in the cause and maintenance of paranoid symptoms.
Transformationally decoupling clustering and tracer bias
Neyrinck, Mark C
2014-01-01
Gaussianizing transformations are used statistically in many non-cosmological fields, but in cosmology, we are only starting to apply them. Here I explain a strategy of analyzing the 1-point function (PDF) of a spatial field, together with the 'essential' clustering statistics of the Gaussianized field, which are invariant to a local transformation. In cosmology, if the tracer sampling is sufficient, this achieves two important goals. First, it can greatly multiply the Fisher information, which is negligible on nonlinear scales in the usual $\\delta$ statistics. Second, it decouples clustering statistics from a local bias description for tracers such as galaxies.
Ditto, Peter H; Wojcik, Sean P; Chen, Eric Evan; Grady, Rebecca Hofstein; Ringel, Megan M
2015-01-01
Duarte et al. are right to worry about political bias in social psychology but they underestimate the ease of correcting it. Both liberals and conservatives show partisan bias that often worsens with cognitive sophistication. More non-liberals in social psychology is unlikely to speed our convergence upon the truth, although it may broaden the questions we ask and the data we collect.
Gender bias in the force concept inventory?
Dietz, R. D.; Pearson, R. H.; Semak, M. R.; Willis, C. W.
2012-02-01
Could the well-established fact that males tend to score higher than females on the Force Concept Inventory (FCI) be due to gender bias in the questions? The eventual answer to the question hinges on the definition of bias. We assert that a question is biased only if a factor other than ability (in this case gender) affects the likelihood that a student will answer the question correctly. The statistical technique of differential item functioning allows us to control for ability in our analysis of student performance on each of the thirty FCI questions. This method uses the total score on the FCI as the measure of ability. We conclude that the evidence for gender bias in the FCI questions is marginal at best.
Sociocognitive Biases in the Evaluation Process.
Perloff, Richard M.; And Others
1980-01-01
Causes of evaluator bias are: overemphasizing concrete, salient, and retrievable information; reporting only evidence which confirms hypothesis; focusing on stable personality factors, rather than on situation and environment; developing positive perceptions of a program as both an evaluator and a highly involved participant; statistical naivete;…
Systematic review of the empirical evidence of study publication bias and outcome reporting bias.
Directory of Open Access Journals (Sweden)
Kerry Dwan
Full Text Available BACKGROUND: The increased use of meta-analysis in systematic reviews of healthcare interventions has highlighted several types of bias that can arise during the completion of a randomised controlled trial. Study publication bias has been recognised as a potential threat to the validity of meta-analysis and can make the readily available evidence unreliable for decision making. Until recently, outcome reporting bias has received less attention. METHODOLOGY/PRINCIPAL FINDINGS: We review and summarise the evidence from a series of cohort studies that have assessed study publication bias and outcome reporting bias in randomised controlled trials. Sixteen studies were eligible of which only two followed the cohort all the way through from protocol approval to information regarding publication of outcomes. Eleven of the studies investigated study publication bias and five investigated outcome reporting bias. Three studies have found that statistically significant outcomes had a higher odds of being fully reported compared to non-significant outcomes (range of odds ratios: 2.2 to 4.7. In comparing trial publications to protocols, we found that 40-62% of studies had at least one primary outcome that was changed, introduced, or omitted. We decided not to undertake meta-analysis due to the differences between studies. CONCLUSIONS: Recent work provides direct empirical evidence for the existence of study publication bias and outcome reporting bias. There is strong evidence of an association between significant results and publication; studies that report positive or significant results are more likely to be published and outcomes that are statistically significant have higher odds of being fully reported. Publications have been found to be inconsistent with their protocols. Researchers need to be aware of the problems of both types of bias and efforts should be concentrated on improving the reporting of trials.
Holm, Håkan J.
2008-01-01
Beliefs in signals that reveal lies or truths are widespread. These signals may lead to a truth or lie detection bias if the probability that such a signal is perceived by the receiver is contingent on the truth value of the sender’s message. Such detection biases are analyzed theoretically in a bluffing game. The detection bias shrinks the equilibrium set to a unique non-pooling equilibrium, in which the better a player is at detecting lies the more often the opponent player will lie. With p...
All your biases belong to us: Breaking RC4 in WPA-TKIP and TLS
Vanhoef, Mathy; Piessens, Frank
2015-01-01
We present new biases in RC4, break the Wi-Fi Protected Access Temporal Key Integrity Protocol (WPA-TKIP), and design a practical plaintext recovery attack against the Transport Layer Security (TLS) protocol. To empirically find new biases in the RC4 keystream we use statistical hypothesis tests. This reveals many new biases in the initial keystream bytes, as well as several new longterm biases. Our fixed-plaintext recovery algorithms are capable of using multiple types of biases, and return ...
DEFF Research Database (Denmark)
Paldam, Martin
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...... 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...
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.
Mishra, Anil V; 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 ...
... 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 ...
Janet Gale Stotsky
1996-01-01
This paper examines the nature of gender bias in tax systems. Gender bias takes both explicit and implicit forms. Explicit gender bias is found in many personal income tax systems. Several countries, especially those in Western Europe, have undertaken to eliminate explicit gender bias in recent years. It is more difficult to identify implicit gender bias, since this depends in large part on value judgments as to desirable social and economic behavior. Implicit gender bias has also been a targ...
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....... 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...... 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...
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...... sizes has been conducted. METHODS: Here, we performed a comprehensive review of meta-analyses of peripheral nongenetic biomarkers that could discriminate individuals with MDD from nondepressed controls. PubMed/MEDLINE, EMBASE, and PsycINFO databases were searched through April 10, 2015. RESULTS: From 15......-analyses, while 11 meta-analyses had evidence of small-study effects. CONCLUSIONS: Our findings suggest that there is an excess of studies with statistically significant results in the literature of peripheral biomarkers for MDD. The selective publication of 'positive studies' and the selective reporting...
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...... protection measure is therefore uniquely suited to capture the full impact of trade policies on relative agricultural price incentives....
Draper, D.
2001-01-01
© 2012 Springer Science+Business Media, LLC. All rights reserved. Article Outline: Glossary Definition of the Subject and Introduction The Bayesian Statistical Paradigm Three Examples Comparison with the Frequentist Statistical Paradigm Future Directions Bibliography
... www.nlm.nih.gov/medlineplus/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 ...
Statistical models for seismic magnitude
Christoffersson, Anders
1980-02-01
In this paper some statistical models in connection with seismic magnitude are presented. Two main situations are treated. The first deals with the estimation of magnitude for an event, using a fixed network of stations and taking into account the detection and bias properties of the individual stations. The second treats the problem of estimating seismicity, and detection and bias properties of individual stations. The models are applied to analyze the magnitude bias effects for an earthquake aftershock sequence from Japan, as recorded by a hypothetical network of 15 stations. It is found that network magnitudes computed by the conventional averaging technique are considerably biased, and that a maximum likelihood approach using instantaneous noise-level estimates for non-detecting stations gives the most consistent magnitude estimates. Finally, the models are applied to evaluate the detection characteristics and associated seismicity as recorded by three VELA arrays: UBO (Uinta Basin), TFO (Tonto Forest) and WMO (Wichita Mountains).
Melita Ambrožič
1991-01-01
The contribution deals with the purpose, beginnings and development of library statistics and the strivings for international standardization in this field. International recommendations are presented, as well as the ISO standard for library statistics. An overview is given of the theoretical contributions and statistical practice in Slovenian librarianship. Cautionary notice on the limitations of the applicability of library statistics in determining library performance is given and the inte...
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.
Casella, George
2002-01-01
"Statistical Inference is a delightfully modern text on statistical theory and deserves serious consideration from every teacher of a graduate- or advanced undergraduate-level first course in statistical theory. . . Chapters 1-5 provide plenty of interesting examples illustrating either the basic concepts of probability or the basic techniques of finding distribution. . . The book has unique features [throughout Chapters 6-12] for example, I have never seen in any comparable text such extensive discussion of ancillary statistics [Ch. 6], including Basu's theorem, dealing with the independence of complete sufficient statistics and ancillary statistics. Basu's theorem is such a useful tool that it should be available to every graduate student of statistics. . . The derivation of the analysis of variance (ANOVA)F test in Chapter 11 via the union-intersection principle is very nice. . . Chapter 12 contains, in addition to the standard regression model, errors-in-variables models. This topic will be of considerabl...
International Nuclear Information System (INIS)
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
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
Forbes, Catherine; Hastings, Nicholas; Peacock, Brian J.
2010-01-01
A new edition of the trusted guide on commonly used statistical distributions Fully updated to reflect the latest developments on the topic, Statistical Distributions, Fourth Edition continues to serve as an authoritative guide on the application of statistical methods to research across various disciplines. The book provides a concise presentation of popular statistical distributions along with the necessary knowledge for their successful use in data modeling and analysis. Following a basic introduction, forty popular distributions are outlined in individual chapters that are complete with re
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
Assessing Bias in Search Engines.
Mowshowitz, Abbe; Kawaguchi, Akira
2002-01-01
Addresses the measurement of bias in search engines on the Web, defining bias as the balance and representation of items in a collection retrieved from a database for a set of queries. Assesses bias by measuring the deviation from the ideal of the distribution produced by a particular search engine. (Author/LRW)
Test Bias and the Elimination of Racism
Sedlacek, William E.
1977-01-01
Three types of test bias are discussed: content bias, atmosphere bias, and use bias. Use bias is considered the most important. Tests reflect the bias in society, and eliminating test bias means eliminating racism and sexism in society. A six-stage model to eliminate racism and sexism is presented. (Author)
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.
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.
Quantifying the Biases of Spectroscopically Selected Gravitational Lenses
Arneson, Ryan A; 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 towards smaller Einstein radius for systems drawn from parent...
The Twelfth Man? Refereeing Bias in English and German Soccer
Babatunde Buraimo; David Forrest; Robert Simmons
2007-01-01
This paper investigates potential bias in awards of player disciplinary sanctions, in the form of cautions (yellow cards) and dismissals (red cards) by referees in the English Premier League and the Bundesliga. Previous studies of behaviour of soccer referees have not adequately incorporated within-game information. Descriptive statistics from our samples clearly show that home teams receive fewer yellow and red cards than away teams. But biases may be wrongly identified where the modeller ha...
The Bias of the Gini Coefficient due to Grouping
VAN OURTI, Tom; Clarke, Philip
2008-01-01
Read also the publication in the 'Review of Economics and Statistics' , 2010, 93(3), 982-994. We 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 remaining second order bias which is useful in empirical analyses. We analyze the empirical performance of our first orde...
Publication Bias ( The "File-Drawer Problem") in Scientific Inference
Scargle, Jeffrey D.; DeVincenzi, Donald (Technical Monitor)
1999-01-01
Publication bias arises whenever the probability that a study is published depends on the statistical significance of its results. This bias, often called the file-drawer effect since the unpublished results are imagined to be tucked away in researchers' file cabinets, is potentially a severe impediment to combining the statistical results of studies collected from the literature. With almost any reasonable quantitative model for publication bias, only a small number of studies lost in the file-drawer will produce a significant bias. This result contradicts the well known Fail Safe File Drawer (FSFD) method for setting limits on the potential harm of publication bias, widely used in social, medical and psychic research. This method incorrectly treats the file drawer as unbiased, and almost always miss-estimates the seriousness of publication bias. A large body of not only psychic research, but medical and social science studies, has mistakenly relied on this method to validate claimed discoveries. Statistical combination can be trusted only if it is known with certainty that all studies that have been carried out are included. Such certainty is virtually impossible to achieve in literature surveys.
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
Ross, Sheldon M
2005-01-01
In this revised text, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, and an explanation of intuition and ideas behind the statistical methods. To quote from the preface, ""It is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data."" Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions and examples.* Ross's clear writin
Ross, Sheldon M
2010-01-01
In this 3rd edition revised text, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, and an explanation of intuition and ideas behind the statistical methods. Concepts are motivated, illustrated and explained in a way that attempts to increase one's intuition. To quote from the preface, ""It is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data."" Ross achieves this
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.
Wannier, Gregory H
2010-01-01
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
Directory of Open Access Journals (Sweden)
Kerry Dwan
Full Text Available BACKGROUND: The increased use of meta-analysis in systematic reviews of healthcare interventions has highlighted several types of bias that can arise during the completion of a randomised controlled trial. Study publication bias and outcome reporting bias have been recognised as a potential threat to the validity of meta-analysis and can make the readily available evidence unreliable for decision making. METHODOLOGY/PRINCIPAL FINDINGS: In this update, we review and summarise the evidence from cohort studies that have assessed study publication bias or outcome reporting bias in randomised controlled trials. Twenty studies were eligible of which four were newly identified in this update. Only two followed the cohort all the way through from protocol approval to information regarding publication of outcomes. Fifteen of the studies investigated study publication bias and five investigated outcome reporting bias. Three studies have found that statistically significant outcomes had a higher odds of being fully reported compared to non-significant outcomes (range of odds ratios: 2.2 to 4.7. In comparing trial publications to protocols, we found that 40-62% of studies had at least one primary outcome that was changed, introduced, or omitted. We decided not to undertake meta-analysis due to the differences between studies. CONCLUSIONS: This update does not change the conclusions of the review in which 16 studies were included. Direct empirical evidence for the existence of study publication bias and outcome reporting bias is shown. There is strong evidence of an association between significant results and publication; studies that report positive or significant results are more likely to be published and outcomes that are statistically significant have higher odds of being fully reported. Publications have been found to be inconsistent with their protocols. Researchers need to be aware of the problems of both types of bias and efforts should be
The Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute works to provide information on cancer statistics in an effort to reduce the burden of cancer among the U.S. population.
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...
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...
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. ...
Baaquie, Belal E.
2012-01-01
A statistical generalization is made of microeconomics in the spirit of going from classical to statistical mechanics. The price and quantity of every commodity1 traded in the market, at each instant of time, is considered to be an independent random variable: all prices and quantities are considered to be stochastic processes, with the observed market prices being a random sample of the stochastic prices. The dynamics of market prices is determined by an action functional and, for concretene...
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. PMID:18324681
Model selection bias and Freedman's paradox
Lukacs, P.M.; Burnham, K.P.; Anderson, D.R.
2010-01-01
In situations where limited knowledge of a system exists and the ratio of data points to variables is small, variable selection methods can often be misleading. Freedman (Am Stat 37:152-155, 1983) demonstrated how common it is to select completely unrelated variables as highly "significant" when the number of data points is similar in magnitude to the number of variables. A new type of model averaging estimator based on model selection with Akaike's AIC is used with linear regression to investigate the problems of likely inclusion of spurious effects and model selection bias, the bias introduced while using the data to select a single seemingly "best" model from a (often large) set of models employing many predictor variables. The new model averaging estimator helps reduce these problems and provides confidence interval coverage at the nominal level while traditional stepwise selection has poor inferential properties. ?? The Institute of Statistical Mathematics, Tokyo 2009.
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.
Measuring nonlocal Lagrangian peak bias
Biagetti, Matteo; Desjacques, Vincent; Paranjape, Aseem
2013-01-01
In the Lagrangian approach to halo clustering, nonlocal bias can be generated either in the initial conditions or by the subsequent gravitational motions. Here, we investigate nonlocal Lagrangian bias contributions involving gradients of the linear density field, for which we have predictions from the excursion set peak formalism. We reformulate this approach in order to explicitly take into account the variable describing the crossing of the collapse barrier. This enables us to write down a bias expansion which includes all the bias terms, including the nonlocal ones. Having checked that the model furnishes a reasonable fit to the halo mass function, we extend the 1-point cross-correlation technique of Musso, Paranjape & Sheth (2012) to bias contributions that are chi-squared distributed. We validate the method with numerical realizations of peaks of Gaussian random fields before applying it to N-body simulations. We focus on the lowest (quadratic) order nonlocal bias factors predicted by the excursion s...
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...
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...
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
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
Freund, Rudolf J; Wilson, William J
2010-01-01
Statistical Methods, 3e provides students with a working introduction to statistical methods offering a wide range of applications that emphasize the quantitative skills useful across many academic disciplines. This text takes a classic approach emphasizing concepts and techniques for working out problems and intepreting results. The book includes research projects, real-world case studies, numerous examples and data exercises organized by level of difficulty. This text requires that a student be familiar with algebra. New to this edition: NEW expansion of exercises a
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
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
Directory of Open Access Journals (Sweden)
Zheng Chunfang
2011-10-01
Full Text Available Abstract Background Paralog reduction, the loss of duplicate genes after whole genome duplication (WGD is a pervasive process. Whether this loss proceeds gene by gene or through deletion of multi-gene DNA segments is controversial, as is the question of fractionation bias, namely whether one homeologous chromosome is more vulnerable to gene deletion than the other. Results As a null hypothesis, we first assume deletion events, on one homeolog only, excise a geometrically distributed number of genes with unknown mean µ, and these events combine to produce deleted runs of length l, distributed approximately as a negative binomial with unknown parameter r, itself a random variable with distribution π(·. A more realistic model requires deletion events on both homeologs distributed as a truncated geometric. We simulate the distribution of run lengths l in both models, as well as the underlying π(r, as a function of µ, and show how sampling l allows us to estimate µ. We apply this to data on a total of 15 genomes descended from 6 distinct WGD events and show how to correct the bias towards shorter runs caused by genome rearrangements. Because of the difficulty in deriving π(· analytically, we develop a deterministic recurrence to calculate each π(r as a function of µ and the proportion of unreduced paralog pairs. Conclusions The parameter µ can be estimated based on run lengths of single-copy regions. Estimates of µ in real data do not exclude the possibility that duplicate gene deletion is largely gene by gene, although it may sometimes involve longer segments.
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’...
Error covariance calculation for forecast bias estimation in hydrologic data assimilation
Pauwels, Valentijn R. N.; De Lannoy, Gabriëlle J. M.
2015-12-01
To date, an outstanding issue in hydrologic data assimilation is a proper way of dealing with forecast bias. A frequently used method to bypass this problem is to rescale the observations to the model climatology. While this approach improves the variability in the modeled soil wetness and discharge, it is not designed to correct the results for any bias. Alternatively, attempts have been made towards incorporating dynamic bias estimates into the assimilation algorithm. Persistent bias models are most often used to propagate the bias estimate, where the a priori forecast bias error covariance is calculated as a constant fraction of the unbiased a priori state error covariance. The latter approach is a simplification to the explicit propagation of the bias error covariance. The objective of this paper is to examine to which extent the choice for the propagation of the bias estimate and its error covariance influence the filter performance. An Observation System Simulation Experiment (OSSE) has been performed, in which ground water storage observations are assimilated into a biased conceptual hydrologic model. The magnitudes of the forecast bias and state error covariances are calibrated by optimizing the innovation statistics of groundwater storage. The obtained bias propagation models are found to be identical to persistent bias models. After calibration, both approaches for the estimation of the forecast bias error covariance lead to similar results, with a realistic attribution of error variances to the bias and state estimate, and significant reductions of the bias in both the estimates of groundwater storage and discharge. Overall, the results in this paper justify the use of the traditional approach for online bias estimation with a persistent bias model and a simplified forecast bias error covariance estimation.
Bergère, M. C.
1999-01-01
We improve Haldane's formula which gives the number of configurations for $N$ particles on $d$ states in a fractional statistic defined by the coupling $g=l/m$. Although nothing is changed in the thermodynamic limit, the new formula makes sense for finite $N=pm+r$ with $p$ integer and $0
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...
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
Challenges of guarantee-time bias.
Giobbie-Hurder, Anita; Gelber, Richard D; Regan, Meredith M
2013-08-10
The potential for guarantee-time bias (GTB), also known as immortal time bias, exists whenever an analysis that is timed from enrollment or random assignment, such as disease-free or overall survival, is compared across groups defined by a classifying event occurring sometime during follow-up. The types of events associated with GTB are varied and may include the occurrence of objective disease response, onset of toxicity, or seroconversion. However, comparative analyses using these types of events as predictors are different from analyses using baseline characteristics that are specified completely before the occurrence of any outcome event. Recognizing the potential for GTB is not always straightforward, and it can be challenging to know when GTB is influencing the results of an analysis. This article defines GTB, provides examples of GTB from several published articles, and discusses three analytic techniques that can be used to remove the bias: conditional landmark analysis, extended Cox model, and inverse probability weighting. The strengths and limitations of each technique are presented. As an example, we explore the effect of bisphosphonate use on disease-free survival (DFS) using data from the BIG (Breast International Group) 1-98 randomized clinical trial. An analysis using a naive approach showed substantial benefit for patients who received bisphosphonate therapy. In contrast, analyses using the three methods known to remove GTB showed no statistical evidence of a reduction in risk of a DFS event with bisphosphonate therapy.
Interloper bias in future large-scale structure surveys
Pullen, Anthony R; Dore, Olivier; Raccanelli, Alvise
2015-01-01
Next-generation spectroscopic surveys will map the large-scale structure of the observable universe, using emission line galaxies as tracers. While each survey will map the sky with a specific emission line, interloping emission lines can masquerade as the survey's intended emission line at different redshifts. Interloping lines from galaxies that are not removed can contaminate the power spectrum measurement, mixing correlations from various redshifts and diluting the true signal. We assess the potential for power spectrum contamination, finding that an interloper fraction worse than 0.2% could bias power spectrum measurements for future surveys by more than 10% of statistical errors, while also biasing inferences based on the power spectrum. We also construct a formalism for predicting biases for cosmological parameter measurements, and we demonstrate that a 0.3% interloper fraction could bias measurements of the growth rate by more than 10% of the error, which can affect constraints from upcoming surveys o...
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
Natrella, Mary Gibbons
2005-01-01
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
B. G. Sidharth
2000-01-01
We consider the recent description of elementary particles in terms of Quantum Mechanical Kerr-Newman Black Holes, a description which provides a rationale for and at the same time reconciles the Bohm-hydrodynamical formulation on the one hand and the Nelsonian stochastiic formulation on the other. The Boson-Fermion divide is discussed, and it is pointed out that in special situations, anomalous statistics, rather than Bose-Einstein or Fermi-Dirac states, can be encountered.
Vardeman, Stephen B.
2003-01-01
In this entry we seek to put into perspective some of the ways in which statistical methods contribute to modern engineering practice. Engineers design and oversee the production, operation, and maintenance of the products and systems that under-gird modern technological society. Their work is built on the foundation of physical (and increasingly biological) science. However, it is of necessity often highly empirical, because there simply isnt scientific theory complete and simple enough to ...
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.
Meneghetti, M; Dahle, H; Limousin, M
2013-01-01
The existence of an arc statistics problem was at the center of a strong debate in the last fifteen years. With the aim to clarify if the optical depth for giant gravitational arcs by galaxy clusters in the so called concordance model is compatible with observations, several studies were carried out which helped to significantly improve our knowledge of strong lensing clusters, unveiling their extremely complex internal structure. In particular, the abundance and the frequency of strong lensing events like gravitational arcs turned out to be a potentially very powerful tool to trace the structure formation. However, given the limited size of observational and theoretical data-sets, the power of arc statistics as a cosmological tool has been only minimally exploited so far. On the other hand, the last years were characterized by significant advancements in the field, and several cluster surveys that are ongoing or planned for the near future seem to have the potential to make arc statistics a competitive cosmo...
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.
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.
Directory of Open Access Journals (Sweden)
Orlov A. I.
2016-05-01
Full Text Available Fuzzy sets are the special form of objects of nonnumeric nature. Therefore, in the processing of the sample, the elements of which are fuzzy sets, a variety of methods for the analysis of statistical data of any nature can be used - the calculation of the average, non-parametric density estimators, construction of diagnostic rules, etc. We have told about the development of our work on the theory of fuzziness (1975 - 2015. In the first of our work on fuzzy sets (1975, the theory of random sets is regarded as a generalization of the theory of fuzzy sets. In non-fiction series "Mathematics. Cybernetics" (publishing house "Knowledge" in 1980 the first book by a Soviet author fuzzy sets is published - our brochure "Optimization problems and fuzzy variables". This book is essentially a "squeeze" our research of 70-ies, ie, the research on the theory of stability and in particular on the statistics of objects of non-numeric nature, with a bias in the methodology. The book includes the main results of the fuzzy theory and its note to the random set theory, as well as new results (first publication! of statistics of fuzzy sets. On the basis of further experience, you can expect that the theory of fuzzy sets will be more actively applied in organizational and economic modeling of industry management processes. We discuss the concept of the average value of a fuzzy set. We have considered a number of statements of problems of testing statistical hypotheses on fuzzy sets. We have also proposed and justified some algorithms for restore relationships between fuzzy variables; we have given the representation of various variants of fuzzy cluster analysis of data and variables and described some methods of collection and description of fuzzy data
1986-01-01
Official population data for the USSR are presented for 1985 and 1986. Part 1 (pp. 65-72) contains data on capitals of union republics and cities with over one million inhabitants, including population estimates for 1986 and vital statistics for 1985. Part 2 (p. 72) presents population estimates by sex and union republic, 1986. Part 3 (pp. 73-6) presents data on population growth, including birth, death, and natural increase rates, 1984-1985; seasonal distribution of births and deaths; birth order; age-specific birth rates in urban and rural areas and by union republic; marriages; age at marriage; and divorces. PMID:12178831
Gender bias in academic recruitment
DEFF Research Database (Denmark)
Abramo, Giovanni; D’Angelo, Ciriaco Andrea; Rosati, Francesco
2016-01-01
It is well known that women are underrepresented in the academic systems of many countries. Gender discrimination is one of the factors that could contribute to this phenomenon. This study considers a recent national academic recruitment campaign in Italy, examining whether women are subject...... to more or less bias than men. The findings show that no gender-related differences occur among the candidates who benefit from positive bias, while among those candidates affected by negative bias, the incidence of women is lower than that of men. Among the factors that determine success in a competition...
Schematic for efficient computation of GC, GC3, and AT3 bias spectra of genome.
Rizvi, Ahsan Z; Venu Gopal, T; Bhattacharya, C
2012-01-01
Selection of synonymous codons for an amino acid is biased in protein translation process. This biased selection causes repetition of synonymous codons in structural parts of genome that stands for high N/3 peaks in DNA spectrum. Period-3 spectral property is utilized here to produce a 3-phase network model based on polyphase filterbank concepts for derivation of codon bias spectra (CBS). Modification of parameters in this model can produce GC, GC3, and AT3 bias spectra. Complete schematic in LabVIEW platform is presented here for efficient and parallel computation of GC, GC3, and AT3 bias spectra of genomes alongwith results of CBS patterns. We have performed the correlation coefficient analysis of GC, GC3, and AT3 bias spectra with codon bias patterns of CBS for biological and statistical significance of this model. PMID:22368390
Statistical properties of randomization in clinical trials.
Lachin, J M
1988-12-01
This is the first of five articles on the properties of different randomization procedures used in clinical trials. This paper presents definitions and discussions of the statistical properties of randomization procedures as they relate to both the design of a clinical trial and the statistical analysis of trial results. The subsequent papers consider, respectively, the properties of simple (complete), permuted-block (i.e., blocked), and urn (adaptive biased-coin) randomization. The properties described herein are the probabilities of treatment imbalances and the potential effects on the power of statistical tests; the permutational basis for statistical tests; and the potential for experimental biases in the assessment of treatment effects due either to the predictability of the random allocations (selection bias) or the susceptibility of the randomization procedure to covariate imbalances (accidental bias). For most randomization procedures, the probabilities of overall treatment imbalances are readily computed, even when a stratified randomization is used. This is important because treatment imbalance may affect statistical power. It is shown, however, that treatment imbalance must be substantial before power is more than trivially affected. The differences between a population versus a permutation model as a basis for a statistical test are reviewed. It is argued that a population model can only be invoked in clinical trials as an untestable assumption, rather than being formally based on sampling at random from a population. On the other hand, a permutational analysis based on the randomization actually employed requires no assumptions regarding the origin of the samples of patients studied. The large sample permutational distribution of the family of linear rank tests is described as a basis for easily conducting a variety of permutation tests. Subgroup (stratified) analyses, analyses when some data are missing, and regression model analyses are also
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…
Selection bias due to parity-conditioning in studies of time trends in fertility
DEFF Research Database (Denmark)
Sallmén, Markku; Bonde, Jens Peter; Lindbohm, Marja-Liisa;
2015-01-01
. METHODS: A study with prospective follow-up was taken as the model to assess the validity of fertility studies. We demonstrate the potential for selection bias using causal graphs and nationwide birth statistics and other demographic data. We tested the existence of parity-conditioning bias in data...
Cognitive biases and language universals
Baronchelli, Andrea; Puglisi, Andrea
2013-01-01
Language universals have been longly attributed to an innate Universal Grammar. An alternative explanation states that linguistic universals emerged independently in every language in response to shared cognitive, though non language-specific, biases. A computational model has recently shown how this could be the case, focusing on the paradigmatic example of the universal properties of color naming patterns, and producing results in accurate agreement with the experimental data. Here we investigate thoroughly the role of a cognitive bias in the framework of this model. We study how, and to what extent, the structure of the bias can influence the corresponding linguistic universal patterns. We show also that the cultural history of a group of speakers introduces population-specific constraints that act against the uniforming pressure of the cognitive bias, and we clarify the interplay between these two forces. We believe that our simulations can help to shed light on the possible mechanisms at work in the evol...
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.
The intentionality bias and schizotypy
Moore, James W.; Pope, A.
2014-01-01
The “intentionality bias” refers to our automatic tendency to judge other people's actions to be intentional. In this experiment we extended research on this effect in two key ways. First, we developed a novel nonlinguistic task for assessing the intentionality bias. This task used video stimuli of ambiguous movements. Second, we investigated the relationship between the strength of this bias and schizotypy (schizophrenia-like symptoms in healthy individuals). Our results showed that the inte...
On the linearity of tracer bias around voids
Pollina, Giorgia; Dolag, Klaus; Weller, Jochen; Baldi, Marco; Moscardini, Lauro
2016-01-01
The large-scale structure of the universe can only be observed directly via luminous tracers of the underlying distribution of dark matter. However, the clustering statistics of tracers are biased and depend on various properties of the tracers themselves, such as their host-halo mass and formation and assembly history. On very large scales, where density fluctuations are within the linear regime, this tracer bias results in a constant offset in the clustering amplitude, which is known as linear bias. Towards smaller non-linear scales, this is no longer the case and tracer bias becomes a complicated function of scale and time. We focus on tracer bias centered on cosmic voids, depressions of the density field that spatially dominate the universe. We consider three different types of tracers: galaxies, galaxy clusters and AGNs, extracted from the hydrodynamical simulation suite Magneticum Pathfinder. In contrast to common clustering statistics that focus on the auto-correlation of tracers, we find that void-tra...
The estimation method of GPS instrumental biases
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
A model of estimating the global positioning system (GPS) instrumental biases and the methods to calculate the relative instrumental biases of satellite and receiver are presented. The calculated results of GPS instrumental biases, the relative instrumental biases of satellite and receiver, and total electron content (TEC) are also shown. Finally, the stability of GPS instrumental biases as well as that of satellite and receiver instrumental biases are evaluated, indicating that they are very stable during a period of two months and a half.
Bias and design in software specifications
Straub, Pablo A.; Zelkowitz, Marvin V.
1990-01-01
Implementation bias in a specification is an arbitrary constraint in the solution space. Presented here is a model of bias in software specifications. Bias is defined in terms of the specification process and a classification of the attributes of the software product. Our definition of bias provides insight into both the origin and the consequences of bias. It also shows that bias is relative and essentially unavoidable. Finally, we describe current work on defining a measure of bias, formalizing our model, and relating bias to software defects.
Publication bias: what is it? How do we measure it? How do we avoid it?
Directory of Open Access Journals (Sweden)
Song F
2013-07-01
Full Text Available Fujian Song, Lee Hooper, Yoon K LokeNorwich Medical School, University of East Anglia, Norwich, UKAbstract: Publication bias occurs when results of published studies are systematically different from results of unpublished studies. The term "dissemination bias" has also been recommended to describe all forms of biases in the research-dissemination process, including outcome-reporting bias, time-lag bias, gray-literature bias, full-publication bias, language bias, citation bias, and media-attention bias. We can measure publication bias by comparing the results of published and unpublished studies addressing the same question. Following up cohorts of studies from inception and comparing publication levels in studies with statistically significant or "positive" results suggested greater odds of formal publication in those with such results, compared to those without. Within reviews, funnel plots and related statistical methods can be used to indicate presence or absence of publication bias, although these can be unreliable in many circumstances. Methods of avoiding publication bias, by identifying and including unpublished outcomes and unpublished studies, are discussed and evaluated. These include searching without limiting by outcome, searching prospective trials registers, searching informal sources, including meeting abstracts and PhD theses, searching regulatory body websites, contacting authors of included studies, and contacting pharmaceutical or medical device companies for further studies. Adding unpublished studies often alters effect sizes, but may not always eliminate publication bias. The compulsory registration of all clinical trials at inception is an important move forward, but it can be difficult for reviewers to access data from unpublished studies located this way. Publication bias may be reduced by journals by publishing high-quality studies regardless of novelty or unexciting results, and by publishing protocols or full
Modeling late entry bias in survival analysis.
Matsuura, Masaaki; Eguchi, Shinto
2005-06-01
In a failure time analysis, we sometimes observe additional study subjects who enter during the study period. These late entries are treated as left-truncated data in the statistical literature. However, with real data, there is a substantial possibility that the delayed entries may have extremely different hazards compared to the other standard subjects. We focus on a situation in which such entry bias might arise in the analysis of survival data. The purpose of the present article is to develop an appropriate methodology for making inference about data including late entries. We construct a model that includes parameters for the effect of delayed entry bias having no specification for the distribution of entry time. We also discuss likelihood inference based on this model and derive the asymptotic behavior of estimates. A simulation study is conducted for a finite sample size in order to compare the analysis results using our method with those using the standard method, where independence between entry time and failure time is assumed. We apply this method to mortality analysis among atomic bomb survivors defined in a geographical study region. PMID:16011705
The Truth and Bias Model of Judgment
West, Tessa V.; Kenny, David A.
2011-01-01
We present a new model for the general study of how the truth and biases affect human judgment. In the truth and bias model, judgments about the world are pulled by 2 primary forces, the truth force and the bias force, and these 2 forces are interrelated. The truth and bias model differentiates force and value, where the force is the strength of…
Measurement Bias Detection through Factor Analysis
Barendse, M. T.; Oort, F. J.; Werner, C. S.; Ligtvoet, R.; Schermelleh-Engel, K.
2012-01-01
Measurement bias is defined as a violation of measurement invariance, which can be investigated through multigroup factor analysis (MGFA), by testing across-group differences in intercepts (uniform bias) and factor loadings (nonuniform bias). Restricted factor analysis (RFA) can also be used to detect measurement bias. To also enable nonuniform…
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.
Information filtering via biased heat conduction
Liu, Jian-Guo; Guo, Qiang
2011-01-01
Heat conduction process has recently found its application in personalized recommendation [T. Zhou \\emph{et al.}, PNAS 107, 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 (BHC), 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% compared with the standard heat conduction algorithm, and the diversity is also 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.
Excess success for three related papers on racial bias.
Francis, Gregory
2015-01-01
Three related articles reported that racial bias altered perceptual experience and influenced decision-making. These findings have been applied to training programs for law enforcement, and elsewhere, to mitigate racial bias. However, a statistical analysis of each of the three articles finds that the reported experimental results should be rare, even if the theoretical ideas were correct. The analysis estimates that the probability of the reported experimental success for the articles is 0.003, 0.048, and 0.070, respectively. These low probabilities suggest that similar future work is unlikely to produce as successful outcomes and indicates that readers should be skeptical about the validity of the reported findings and their theoretical implications. The reported findings should not be used to guide policies related to racial bias, and new experimental work is needed to judge the merit of the theoretical ideas. PMID:25983701
Excess success for three related papers on racial bias
Directory of Open Access Journals (Sweden)
Gregory eFrancis
2015-05-01
Full Text Available Three related articles reported that racial bias altered perceptual experience and influenced decision-making. These findings have been applied to training programs for law enforcement, and elsewhere, to mitigate racial bias. However, a statistical analysis of each of the three articles finds that the reported experimental results should be rare, even if the theoretical ideas were correct. The analysis estimates that the probability of the reported experimental success for the articles is 0.003, 0.048, and 0.070, respectively. These low probabilities suggest that similar future work is unlikely to produce as successful outcomes and indicates that readers should be skeptical about the validity of the reported findings and their theoretical implications. The reported findings should not be used to guide policies related to racial bias, and new experimental work is needed to judge the merit of the theoretical ideas.
Assessing bias in osteoarthritis trials included in Cochrane reviews
DEFF Research Database (Denmark)
Hansen, Julie B; Juhl, Carsten Bogh; Boutron, Isabelle;
2014-01-01
INTRODUCTION: The validity of systematic reviews and meta-analysis depends on methodological quality and unbiased dissemination of trials. Our objective is to evaluate the association of estimates of treatment effects with different bias-related study characteristics in meta-analyses of intervent......INTRODUCTION: The validity of systematic reviews and meta-analysis depends on methodological quality and unbiased dissemination of trials. Our objective is to evaluate the association of estimates of treatment effects with different bias-related study characteristics in meta......-squared) as a consequence of inclusion in the mixed effects statistical model. ETHICS AND DISSEMINATION: Meta-analyses and randomised controlled trials provide the most reliable basis for treatment of patients with OA, but the actual impact of bias is unclear. This study will systematically examine the methodological...
Inference for blocked randomization under a selection bias model.
Kennes, Lieven N; Rosenberger, William F; Hilgers, Ralf-Dieter
2015-12-01
We provide an asymptotic test to analyze randomized clinical trials that may be subject to selection bias. For normally distributed responses, and under permuted block randomization, we derive a likelihood ratio test of the treatment effect under a selection bias model. A likelihood ratio test of the presence of selection bias arises from the same formulation. We prove that the test is asymptotically chi-square on one degree of freedom. These results correlate well with the likelihood ratio test of Ivanova et al. (2005, Statistics in Medicine 24, 1537-1546) for binary responses, for which they established by simulation that the asymptotic distribution is chi-square. Simulations also show that the test is robust to departures from normality and under another randomization procedure. We illustrate the test by reanalyzing a clinical trial on retinal detachment. PMID:26099068
Saito, Shun; Vlah, Zvonimir; Seljak, Uroš; Okumura, Teppei; McDonald, Patrick
2014-01-01
Understanding the relation between underlying matter distribution and biased tracers such as galaxy or dark matter halo is essential to extract cosmological information from ongoing or future galaxy redshift surveys. At sufficiently large scales such as the BAO scale, a standard approach for the bias problem on the basis of the perturbation theory (PT) is to assume the `local bias' model in which the density field of biased tracers is deterministically expanded in terms of matter density field at the same position. The higher-order bias parameters are then determined by combining the power spectrum with higher-order statistics such as the bispectrum. As is pointed out by recent studies, however, nonlinear gravitational evolution naturally induces nonlocal bias terms even if initially starting only with purely local bias. As a matter of fact, previous works showed that the second-order nonlocal bias term, which corresponds to the gravitational tidal field, is important to explain the characteristic scale-depen...
Longman, Richard W.; Bergmann, Martin; Juang, Jer-Nan
1988-01-01
For the ERA system identification algorithm, perturbation methods are used to develop expressions for variance and bias of the identified modal parameters. Based on the statistics of the measurement noise, the variance results serve as confidence criteria by indicating how likely the true parameters are to lie within any chosen interval about their identified values. This replaces the use of expensive and time-consuming Monte Carlo computer runs to obtain similar information. The bias estimates help guide the ERA user in his choice of which data points to use and how much data to use in order to obtain the best results, performing the trade-off between the bias and scatter. Also, when the uncertainty in the bias is sufficiently small, the bias information can be used to correct the ERA results. In addition, expressions for the variance and bias of the singular values serve as tools to help the ERA user decide the proper modal order.
Bias in Dynamic Monte Carlo Alpha Calculations
Energy Technology Data Exchange (ETDEWEB)
Sweezy, Jeremy Ed [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Nolen, Steven Douglas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Adams, Terry R. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Trahan, Travis John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2015-02-06
A 1/N bias in the estimate of the neutron time-constant (commonly denoted as α) has been seen in dynamic neutronic calculations performed with MCATK. In this paper we show that the bias is most likely caused by taking the logarithm of a stochastic quantity. We also investigate the known bias due to the particle population control method used in MCATK. We conclude that this bias due to the particle population control method is negligible compared to other sources of bias.
Statistical Methods for Material Characterization and Qualification
Energy Technology Data Exchange (ETDEWEB)
Kercher, A.K.
2005-04-01
This document describes a suite of statistical methods that can be used to infer lot parameters from the data obtained from inspection/testing of random samples taken from that lot. Some of these methods will be needed to perform the statistical acceptance tests required by the Advanced Gas Reactor Fuel Development and Qualification (AGR) Program. Special focus has been placed on proper interpretation of acceptance criteria and unambiguous methods of reporting the statistical results. In addition, modified statistical methods are described that can provide valuable measures of quality for different lots of material. This document has been written for use as a reference and a guide for performing these statistical calculations. Examples of each method are provided. Uncertainty analysis (e.g., measurement uncertainty due to instrumental bias) is not included in this document, but should be considered when reporting statistical results.
Statistical methods for material characterization and qualification
Energy Technology Data Exchange (ETDEWEB)
Hunn, John D [ORNL; Kercher, Andrew K [ORNL
2005-01-01
This document describes a suite of statistical methods that can be used to infer lot parameters from the data obtained from inspection/testing of random samples taken from that lot. Some of these methods will be needed to perform the statistical acceptance tests required by the Advanced Gas Reactor Fuel Development and Qualification (AGR) Program. Special focus has been placed on proper interpretation of acceptance criteria and unambiguous methods of reporting the statistical results. In addition, modified statistical methods are described that can provide valuable measures of quality for different lots of material. This document has been written for use as a reference and a guide for performing these statistical calculations. Examples of each method are provided. Uncertainty analysis (e.g., measurement uncertainty due to instrumental bias) is not included in this document, but should be considered when reporting statistical results.
International Nuclear Information System (INIS)
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)
Perception bias in route choice
Vreeswijk, J.D.; Thomas, T.; Berkum, van E.C.; Arem, van B.
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 non-
Microturbulence measurements during divertor biasing
International Nuclear Information System (INIS)
The application of a bias voltage to a neutralization plate of the upper divertor with respect to the vacuum chamber in the Tokamak de Varennes (TdeV) influences the plasma well inside the separatrix. In particular, the unbiased Ohmic poloidal rotation edge velocity measured by visible spectroscopy is found to be in the electron diamagnetic drift direction (2-3 km/s) and increases by a factor of two for Vbias = 100 V. This coincides with a major reduction of the microturbulence signal at low frequencies (50 kHz -1 -1), as determined from coherent laser scattering measurements. One possible explanation is that the turbulence signal is simply Doppler shifted to frequencies outside the accessible range. This scenario is, however, difficult to reconcile with some observations. Another explanation invokes a reduction of the turbulence level. The variation of the turbulence signal as a function of the applied bias voltage can indeed be reproduced with a theoretical model based on radial and poloidal decorrelation mechanisms, the latter corresponding to poloidal velocity shear stabilization. This model also explains the observed steepening of the k-spectrum decay during biasing. Biasing also modifies the electron density profile inside the separatrix. These changes of nabla ne cannot explain the behaviour of microturbulence behaviour, when explained in terms of stabilization, would agree with the plasma maintaining a steeper electron density gradient. (author). 17 refs, 9 figs
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. PMID:26528208
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.
Stereotype Formation : Biased by Association
Le Pelley, Mike E.; Reimers, Stian J.; Calvini, Guglielmo; Spears, Russell; Beesley, Tom; Murphy, Robin A.
2010-01-01
We propose that biases in attitude and stereotype formation might arise as a result of learned differences ill the extent its which social groups have previously been predictive elf behavioral or physical properties Experiments 1 and 2 demonstrate that differences in the experienced predictiveness o
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.
Evaluating a Combined Bias Correction and Stochastic Downscaling Method
Volosciuk, Claudia; Maraun, Douglas; Vrac, Mathieu; Widmann, Martin
2016-04-01
Much of our knowledge about future changes in precipitation relies on global (GCM) and/or regional climate models (RCM) that have resolutions which are much coarser than typical spatial scales of extreme precipitation. The major problems with these projections are both climate model biases and the scale gap between grid box and point scale. Wong et al. presented a first attempt to jointly bias correct and downscale precipitation at daily scales. This approach however relied on spectrally nudged RCM simulations and was not able to post-process GCM biases. Previously, we have presented an extension of this approach that separates the downscaling from the bias correction and in principle is applicable to free running RCMs, such as those available from ENSEMBLES or CORDEX. In a first step, we bias correct the RCMs (EURO-CORDEX) against gridded observational datasets (e.g., E-OBS) at the same scale using a quantile mapping approach that relies on distribution transformation. To correct the whole precipitation distribution including extreme tails we apply a mixture distribution of a gamma distribution for the precipitation mass and a generalized Pareto distribution for the extreme tail. In a second step, we bridge the scale gap: we add small scale variability to the bias corrected precipitation time series using a vector generalized linear gamma model (VGLM gamma). To calibrate the VGLM gamma model we determine the statistical relationship between precipitation observations on different scales, i.e. between gridded (e.g., E-OBS) and station (ECA&D) observations. Here we present a comprehensive evaluation of this approach against 86 weather stations in Europe based on the VALUE perfect predictor experiment, including a comparison with standard bias correction techniques.
Statistical analysis of angular correlation measurements
International Nuclear Information System (INIS)
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)
Bias Adjusted Precipitation Threat Scores
Directory of Open Access Journals (Sweden)
F. Mesinger
2008-04-01
Full Text Available Among the wide variety of performance measures available for the assessment of skill of deterministic precipitation forecasts, the equitable threat score (ETS might well be the one used most frequently. It is typically used in conjunction with the bias score. However, apart from its mathematical definition the meaning of the ETS is not clear. It has been pointed out (Mason, 1989; Hamill, 1999 that forecasts with a larger bias tend to have a higher ETS. Even so, the present author has not seen this having been accounted for in any of numerous papers that in recent years have used the ETS along with bias "as a measure of forecast accuracy".
A method to adjust the threat score (TS or the ETS so as to arrive at their values that correspond to unit bias in order to show the model's or forecaster's accuracy in extit{placing} precipitation has been proposed earlier by the present author (Mesinger and Brill, the so-called dH/dF method. A serious deficiency however has since been noted with the dH/dF method in that the hypothetical function that it arrives at to interpolate or extrapolate the observed value of hits to unit bias can have values of hits greater than forecast when the forecast area tends to zero. Another method is proposed here based on the assumption that the increase in hits per unit increase in false alarms is proportional to the yet unhit area. This new method removes the deficiency of the dH/dF method. Examples of its performance for 12 months of forecasts by three NCEP operational models are given.
Systematic Bias in Cosmic Shear: Beyond the Fisher Matrix
Amara, Adam
2007-01-01
We describe a method for computing the biases that systematic signals introduce in parameter estimation using a simple extension of the Fisher matrix formalism. This allows us to calculate the offset of the best fit parameters relative to the fiducial model, in addition to the usual statistical error ellipse. As an application, we study the impact that residual systematics in tomographic weak lensing measurements. In particular we explore three different types of shape measurement systematics: (i) additive systematic with no redshift evolution; (ii) additive systematic with redshift evolution; and (iii) multiplicative systematic. In each case, we consider a wide range of scale dependence and redshift evolution of the systematics signal. For a future DUNE-like full sky survey, we find that, for cases with mild redshift evolution, the variance of the additive systematic signal should be kept below 10^-7 to ensure biases on cosmological parameters that are sub-dominant to the statistical errors. For the multipli...
Thompson, Michael; Owen, Linda; Wilkinson, Kate; Wood, Roger; Damant, Andrew
2004-12-01
Bias between the Dumas and the Kjeldahl methods for the determination of protein nitrogen in food was studied by conducting an interlaboratory study involving 40 laboratories and 20 different test materials. Biases were found to be small and statistically significant only for the chicken test materials, where a bias of 0.020±0.004% m/m was detected.
Cosmetic Plastic Surgery Statistics
2014 Cosmetic Plastic Surgery Statistics Cosmetic Procedure Trends 2014 Plastic Surgery Statistics Report Please credit the AMERICAN SOCIETY OF PLASTIC SURGEONS when citing statistical data or using ...
On Infinite Quon Statistics and "Ambiguous" Statistics
Meljanac, S.; Milekovic, M.; Ristic, R.
1999-01-01
We critically examine a recent suggestion that "ambiguous" statistics is equivalent to infinite quon statistics and that it describes a dilute, nonrelativistics ideal gas of extremal black holes. We show that these two types of statistics are different and that the description of extremal black holes in terms of "ambiguous" statistics cannot be applied.
Belief bias and relational reasoning.
Roberts, Maxwell J; Sykes, Elizabeth D A
2003-01-01
When people evaluate categorical syllogisms, they tend to reject unbelievable conclusions and accept believable ones irrespective of their validity. Typically, this effect is particularly marked for invalid conclusions that are possible, but do not necessarily follow, given the premises. However, smaller believability effects can also be detected for other types of conclusion. Three experiments are reported here, in which an attempt was made to determine whether belief bias effects can manifest themselves on the relational inference task. Subjects evaluated the validity of conclusions such as William the Conqueror was king after the Pyramids were built (temporal task) or Manchester is north of Bournemouth (spatial task) with respect to their premises. All of the major findings for equivalent categorical syllogism tasks were replicated. However, the overall size of the main effect of believability appears to be related to task presentation, a phenomenon not previously identified for categorical syllogisms and which current theories of belief bias have difficulty explaining.
International Nuclear Information System (INIS)
The origin of the exchange bias phenomenon is investigated on the basis of a quantum mechanical model. In particular, the mechanisms that determine the magnetic structure in the vicinity of an antiferromagnetic-ferromagnetic interface are reexamined. This way we establish how the breaking of translational invariance modifies quantum spin fluctuations. It is found that non-uniform fluctuations induce uncompensated spins in the antiferromagnet, which in turn give rise to a dipole field that couples to the magnetization of the ferromagnet. This coupling yields an exchange bias field that is of the order of magnitude of the one observed experimentally. A net surface magnetization should also be experimentally observable in a clean antiferromagnetic surface
Opinion Dynamics with Confirmation Bias
Allahverdyan, A E
2014-01-01
Background: 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. Methodology/Principal Findings: 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 preferenc...
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.
Cosmological Evolution of Linear Bias
Basilakos, S; Basilakos, Spyros; Plionis, Manolis
2000-01-01
Using linear perturbation theory and the Friedmann-Lemaitre solutions of the cosmological field equations, we derive analytically a second-order differential equation for the evolution of the linear bias factor, b(z), between the background matter and a mass-tracer fluctuation field. We find b(z) to be a strongly dependent function of redshift in all cosmological models. Comparing our analytical solution with the semi-analytic model of Mo & White, which utilises the Press-Schechter formalism and the gravitationally induced evolution of clustering, we find an extremely good agreement even at large redshifts, once we normalize to the same bias value at two different epochs, one of which is the present. Furthermore, our analytic b(z) function agrees well with the outcome of N-body simulations even up to large redshifts.
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.
Investigating Endogeneity Bias in Marketing
Qing Liu; Thomas Otter; Greg M. Allenby
2007-01-01
The use of adaptive designs in conjoint analysis has been shown to lead to an endogeneity bias in part-worth estimates using sampling experiments. In this paper, we re-examine the endogeneity issue in light of the likelihood principle. The likelihood principle asserts that all relevant information in the data about model parameters is contained in the likelihood function. We show that, once the data are collected, adhering to the likelihood principle leads to analysis where endogeneity become...
Opinion Dynamics with Confirmation Bias
Allahverdyan, Armen E.; Aram Galstyan
2014-01-01
Background: 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. Methodology/Principal Findings: We formulate a (non-Bayesian) model for revising subjective proba...
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.
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. PMID:15807044
Correcting power and p-value calculations for bias in diffusion tensor imaging.
Lauzon, Carolyn B; Landman, Bennett A
2013-07-01
Diffusion tensor imaging (DTI) provides quantitative parametric maps sensitive to tissue microarchitecture (e.g., fractional anisotropy, FA). These maps are estimated through computational processes and subject to random distortions including variance and bias. Traditional statistical procedures commonly used for study planning (including power analyses and p-value/alpha-rate thresholds) specifically model variability, but neglect potential impacts of bias. Herein, we quantitatively investigate the impacts of bias in DTI on hypothesis test properties (power and alpha-rate) using a two-sided hypothesis testing framework. We present theoretical evaluation of bias on hypothesis test properties, evaluate the bias estimation technique SIMEX for DTI hypothesis testing using simulated data, and evaluate the impacts of bias on spatially varying power and alpha rates in an empirical study of 21 subjects. Bias is shown to inflame alpha rates, distort the power curve, and cause significant power loss even in empirical settings where the expected difference in bias between groups is zero. These adverse effects can be attenuated by properly accounting for bias in the calculation of power and p-values. PMID:23465764
A Pharmacological Primer of Biased Agonism
Andresen1, Bradley T.
2011-01-01
Biased agonism is one of the fastest growing topics in G protein-coupled receptor pharmacology; moreover, biased agonists are used in the clinic today: carvedilol (Coreg®) is a biased agonist of beta-adrenergic receptors. However, there is a general lack of understanding of biased agonism when compared to traditional pharmacological terminology. Therefore, this review is designed to provide a basic introduction to classical pharmacology as well as G protein-coupled receptor signal transductio...
Galaxy peculiar velocities and evolution-bias
Percival, Will; Schafer, B.
2007-01-01
Galaxy bias can be split into two components: a formation-bias based on the locations of galaxy creation, and an evolution-bias that details their subsequent evolution. In this letter we consider evolution-bias in the peaks model. In this model, galaxy formation takes place at local maxima in the density field, and we analyse the subsequent peculiar motion of these galaxies in a linear model of structure formation. The peak restriction yields differences in the velocity distribution and corre...
Selection bias in rheumatic disease research
Choi, Hyon K.; Nguyen, Uyen-Sa; Niu, Jingbo; Danaei, Goodarz; Zhang, Yuqing
2014-01-01
The identification of modifiable risk factors for the development of rheumatic conditions and their sequelae is crucial for reducing the substantial worldwide burden of these diseases. However, the validity of such research can be threatened by sources of bias, including confounding, measurement and selection biases. In this Review, we discuss potentially major issues of selection bias—a type of bias frequently overshadowed by other bias and feasibility issues, despite being equally or more p...
Quantifying selective reporting and the Proteus phenomenon for multiple datasets with similar bias.
Directory of Open Access Journals (Sweden)
Thomas Pfeiffer
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
Culturally Biased Assumptions in Counseling Psychology
Pedersen, Paul B.
2003-01-01
Eight clusters of culturally biased assumptions are identified for further discussion from Leong and Ponterotto's (2003) article. The presence of cultural bias demonstrates that cultural bias is so robust and pervasive that is permeates the profession of counseling psychology, even including those articles that effectively attack cultural bias…
Biased managers, organizational design, and incentive provision
Moreira, Humberto Ataíde; Costa, Cristiano Machado; Ferreira, Daniel Bernardo Soares
2004-01-01
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.
Spallation neutron source RF cavity bias system
International Nuclear Information System (INIS)
The Spallation Neutron Source r.f. cavity bias system is described under the topic headings: bias system, r.f. cavity, cables, d.c. bias power supply, transistor regulator and control system. Calculation of 4 core 300 mm solid aluminium cable inductance, coaxial shunt frequency response and transistor regulator computed frequency response, are discussed in appendices 1-3. (U.K.)
Begging the Question: Is Critical Thinking Biased?
Alston, Kal
1995-01-01
Discusses whether critical thinking is biased, examining what is meant by critical thinking and bias and what the consequences are for addressing bias in different ways. The paper responds to the three previous papers in the critical thinking symposium in this issue of the journal. (SM)
Attentional bias predicts heroin relapse following treatment
M.A.E. Marissen; I.H.A. Franken; A.J. Waters; P. Blanken; W. van den Brink; V.M. Hendriks
2006-01-01
Aims Previous studies have shown that abstinent heroin addicts exhibit an attentional bias to heroin-related stimuli. It has been suggested that attentional bias may represent a vulnerability to relapse into drug use. In the present study, the predictive value of pre-treatment attentional bias on re
Andrich, David; Marais, Ida; Humphry, Stephen Mark
2016-01-01
Recent research has shown how the statistical bias in Rasch model difficulty estimates induced by guessing in multiple-choice items can be eliminated. Using vertical scaling of a high-profile national reading test, it is shown that the dominant effect of removing such bias is a nonlinear change in the unit of scale across the continuum. The…
DiPonio, Joseph M.
2010-01-01
The primary object of this study was to determine whether racial and/or gender bias were evidenced in the use of the ICIS-Principal. Specifically, will the use of the ICIS-Principal result in biased scores at a statistically significant level when rating current practicing administrators of varying gender and race. The study involved simulated…
A Review of Studies on Media Bias at Home
Institute of Scientific and Technical Information of China (English)
辛一丹
2015-01-01
Bias is widely existed nowadays.Domestic scholars have done a lot of research on the bias,especially the media bias.They studied the media bias from different perspectives,such as the bias on China image,the bias of a certain media FOX,the bias on the venerable group,the bias on women and so on.The author plans to give a review of the studies on media bias at home in this paper.
A Review of Studies on Media Bias at Home
Institute of Scientific and Technical Information of China (English)
辛一丹
2015-01-01
Bias is widely existed nowadays. Domestic scholars have done a lot of research on the bias, especially the media bias. They studied the media bias from different perspectives, such as the bias on China image,the bias of a certain media FOX, the bias on the venerable group, the bias on women and so on. The author plans to give a review of the studies on media bias at home in this paper.
Introducing Decorated HODs: modeling assembly bias in the galaxy-halo connection
Hearin, Andrew P; Bosch, Frank C van den; Campbell, Duncan; Tollerud, Erik
2015-01-01
The connection between galaxies and dark matter halos is often inferred from data using probabilistic models, such as the Halo Occupation Distribution (HOD). Conventional HOD formulations assume that only halo mass governs the galaxy-halo connection. Violations of this assumption, known as galaxy assembly bias, threaten the HOD program. We introduce decorated HODs, a new, flexible class of models designed to account for assembly bias. Decorated HODs minimally expand the parameter space and maximize the independence between traditional and novel HOD parameters. We use decorated HODs to quantify the influence of assembly bias on clustering and lensing statistics. For SDSS-like samples, the impact of assembly bias on galaxy clustering can be as large as a factor of two on r ~ 200 kpc scales and ~15% in the linear regime. Assembly bias can either enhance or diminish clustering on large scales, but generally increases clustering on scales r <~ 1 Mpc. We performed our calculations with Halotools, an open-source,...
MODIS/Aqua 8-Day Clear Sky Radiance Bias Daily L3 Global 1Deg Zonal Bands V006
National Aeronautics and Space Administration — MODIS 8-day clear-sky radiance bias (observed - calculated) statistics are provided for 1Deg latitudinal zones and selected thermal bands. Separation by day and...
Separate Universe Consistency Relation and Calibration of Halo Bias
Li, Yin; Takada, Masahiro
2015-01-01
Linear halo bias is the response of dark matter halo number density to a long wavelength fluctuation in the dark matter density. Using abundance matching between separate universe simulations which absorb the latter into a change in the background, we test the consistency relation between the change in a one point function, the halo mass function, and a two point function, the halo-matter cross correlation in the long wavelength limit. We find excellent agreement between the two at the $1-2\\%$ level for average halo biases between $1 \\lesssim \\bar b_1 \\lesssim 4$ and no statistically significant deviations at the $4-5\\%$ level out to $\\bar b_1 \\approx 8$. The separate universe technique provides a way of calibrating linear halo bias efficiently for even highly biased rare halos in the $\\Lambda$CDM model. Observational violation of the consistency relation would indicate new physics, e.g.~in the dark matter, dark energy or primordial non-Gaussianity sectors.
Analysis of the theoretical bias in dark matter direct detection
International Nuclear Information System (INIS)
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
Koyama, Toshiyuki; Yamaji, Atsushi; Sato, Katsushi
2012-01-01
Linear structures perpendicular to an outcrop surface are easily discovered, but those parallel to the surface are not, giving rise to a biased orientation distribution of the structures. Here, we propose a bias correction method: Statistical inversion was conducted to unbias the distribution of the axes of mesoscale slump folds in the Cretaceous Izumi Group, Japan using the orientation distribution of outcrop surfaces. The observed axes showed a cluster in the SE quadrant. Their unbiased dis...
The Evolution of Rotation Group Bias: Will the Real Unemployment Rate Please Stand Up?
Alan B. Krueger; Mas, Alexandre; Niu, Xiaotong
2014-01-01
This paper documents that rotation group bias -- the tendency for labor force statistics to vary systematically by month in sample in labor force surveys -- in the Current Population Survey (CPS) has worsened considerably over time. The estimated unemployment rate for earlier rotation groups has grown sharply relative to the unemployment rate for later rotation groups; both should be nationally representative samples. The rise in rotation group bias is driven by a growing tendency for respond...
A Biased Review of Sociophysics
Stauffer, Dietrich
2013-04-01
Various aspects of recent sociophysics research are shortly reviewed: Schelling model as an example for lack of interdisciplinary cooperation, opinion dynamics, combat, and citation statistics as an example for strong interdisciplinarity.
A Biased Review of Sociophysics
Stauffer, Dietrich
2012-01-01
Various aspects of recent sociophysics research are shortly reviewed: Schelling model as an example for lack of interdisciplinary cooperation, opinion dynamics, combat, and citation statistics as an example for strong interdisciplinarity.
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...
Leyrat, C; Caille, A; Donner, A; Giraudeau, B
2013-08-30
Cluster randomized trials (CRTs) are often prone to selection bias despite randomization. Using a simulation study, we investigated the use of propensity score (PS) based methods in estimating treatment effects in CRTs with selection bias when the outcome is quantitative. Of four PS-based methods (adjustment on PS, inverse weighting, stratification, and optimal full matching method), three successfully corrected the bias, as did an approach using classical multivariable regression. However, they showed poorer statistical efficiency than classical methods, with higher standard error for the treatment effect, and type I error much smaller than the 5% nominal level. PMID:23553813
Statistical theory of Internet exploration
Dall'Asta, Luca; Alvarez-Hamelin, Ignacio; Barrat, Alain; Vázquez, Alexei; Vespignani, Alessandro
2005-03-01
The general methodology used to construct Internet maps consists in merging all the discovered paths obtained by sending data packets from a set of active computers to a set of destination hosts, obtaining a graphlike representation of the network. This technique, sometimes referred to as Internet tomography, spurs the issue concerning the statistical reliability of such empirical maps. We tackle this problem by modeling the network sampling process on synthetic graphs and by using a mean-field approximation to obtain expressions for the probability of edge and vertex detection in the sampled graph. This allows a general understanding of the origin of possible sampling biases. In particular, we find a direct dependence of the map statistical accuracy upon the topological properties (in particular, the betweenness centrality property) of the underlying network. In this framework, it appears that statistically heterogeneous network topologies are captured better than the homogeneous ones during the mapping process. Finally, the analytical discussion is complemented with a thorough numerical investigation of simulated mapping strategies in network models with varying topological properties.
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.
... Shop With CureSearch Blog Donate Now Select Page Childhood Cancer Statistics Home > Understanding Children’s Cancer > Childhood Cancer Statistics Childhood Cancer Statistics – Graphs and Infographics Number of Diagnoses ...
Neuroendocrine Tumor: Statistics
... Tumor > Neuroendocrine Tumor - Statistics Request Permissions Neuroendocrine Tumor - Statistics Approved by the Cancer.Net Editorial Board , 04/ ... the body. It is important to remember that statistics on how many people survive this type of ...
... Cost Global More Prevalence Disability Suicide Cost Global Statistics Understanding the scope of mental illnesses and their ... those affected receive treatment. The information on these statistics pages includes the best statistics currently available on ...
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.
Weak Lensing Peak Finding: Estimators, Filters, and Biases
Schmidt, Fabian
2010-01-01
Large catalogs of shear-selected peaks have recently become a reality. In order to properly interpret the abundance and properties of these peaks, it is necessary to take into account the effects of the clustering of source galaxies, among themselves and with the lens. In addition, the preferred selection of lensed galaxies in a flux- and size-limited sample leads to fluctuations in the apparent source density which correlate with the lensing field (lensing bias). In this paper, we investigate these issues for two different choices of shear estimators which are commonly in use today: globally-normalized and locally-normalized estimators. While in principle equivalent, in practice these estimators respond differently to systematic effects such as lensing bias and cluster member dilution. Furthermore, we find that which estimator is statistically superior depends on the specific shape of the filter employed for peak finding; suboptimal choices of the estimator+filter combination can result in a suppression of t...
Eddington-Malmquist bias in a cosmological context
Teerikorpi, P
2015-01-01
In 1914, Eddington derived a formula for the difference between the mean absolute magnitudes of stars "in space" or gathered "from the sky". Malmquist (1920) derived a general relation for this difference in Euclidean space. Here we study this statistical bias in cosmology, clarifying and expanding previous work. We derived the Malmquist relation within a general cosmological framework, including Friedmann's model, analogously to the way Malmquist showed in 1936 that his formula is also valid in the presence of extinction in Euclidean space. We also discuss some conceptual aspects that explain the wide scope of the bias relation. The Malmquist formula for the intrinsic difference _m - M_0 = - sigma_M^2 dlna(m)/dm is also valid for observations made in an expanding Friedmann universe. This is holds true for bolometric and finite-band magnitudes when a(m) refers to the distribution of observed (uncorrected for K-effect or z-dependent extinction) apparent magnitudes.
Algebraic statistics computational commutative algebra in statistics
Pistone, Giovanni; Wynn, Henry P
2000-01-01
Written by pioneers in this exciting new field, Algebraic Statistics introduces the application of polynomial algebra to experimental design, discrete probability, and statistics. It begins with an introduction to Gröbner bases and a thorough description of their applications to experimental design. A special chapter covers the binary case with new application to coherent systems in reliability and two level factorial designs. The work paves the way, in the last two chapters, for the application of computer algebra to discrete probability and statistical modelling through the important concept of an algebraic statistical model.As the first book on the subject, Algebraic Statistics presents many opportunities for spin-off research and applications and should become a landmark work welcomed by both the statistical community and its relatives in mathematics and computer science.
Selection bias in rheumatic disease research
Choi, Hyon K.; Nguyen, Uyen-Sa; Niu, Jingbo; Danaei, Goodarz; Zhang, Yuqing
2014-01-01
The identification of modifiable risk factors for the development of rheumatic conditions and their sequelae is crucial for reducing the substantial worldwide burden of these diseases. However, the validity of such research can be threatened by sources of bias, including confounding, measurement and selection biases. In this Review, we discuss potentially major issues of selection bias—a type of bias frequently overshadowed by other bias and feasibility issues, despite being equally or more problematic—in key areas of rheumatic disease research. We present index event bias (a type of selection bias) as one of the potentially unifying reasons behind some unexpected findings, such as the ‘risk factor paradox’—a phenomenon exemplified by the discrepant effects of certain risk factors on the development versus the progression of osteoarthritis (OA) or rheumatoid arthritis (RA). We also discuss potential selection biases owing to differential loss to follow-up in RA and OA research, as well as those due to the depletion of susceptibles (prevalent user bias) and immortal time bias. The lesson remains that selection bias can be ubiquitous and, therefore, has the potential to lead the field astray. Thus, we conclude with suggestions to help investigators avoid such issues and limit the impact on future rheumatology research. PMID:24686510
Official statistical publications and economic statistics
Mavis Anagboso; Allan Flowers; Geoff Tily; Gavin Wallis
2007-01-01
Introduces the new journal and provides a retrospective review of compendia publications of official statistics and analysis.Since its first publication in 1953, Economic Trends and its companion labour market publications have recordedchanges to the UK economy and labour market. In this new publication, Economic & Labour Market Review,the Office for National Statistics brings these two fields of economic statistics into a single publication. As patterns ofeconomic activity and work change, t...
Hindsight bias and investment decisions making empirical evidence form an emerging financial market
Directory of Open Access Journals (Sweden)
Muntazir Hussain
2013-05-01
Full Text Available We studied the hindsight bias and investor decision making by employing the novel approach asset selection effect and sign of return effect. The study investigated the hindsight bias and investor decision making through questionnaires. The respondents are divided into three groups namely bank financial managers, stock market investors and students. The statistical significance of the asset selection effect and sign of return effect is tested by proportional z-test. Furthermore, the correlation of the memory error and recall error is also determined. The overall perceived error (hindsight bias relationship is checked with the confidence in recall and confidence in estimate. We found strong evidence of hindsight bias in all respondents groups and its worst consequence on investment decision making. The bank financial managers were found less exposed to hindsight bias in comparison to stock market investors in asset selection effect. However, in sign of return effect the financial managers were more hindsight biased than the stock market investors. The relationship of hindsight bias and confidence in recall and confidence in estimate also confirms that all the respondents were hindsight biased and more confident in their estimate and less confident in their recall. All the respondents claim that they knew the phenomenon all along are wrong in their estimate. The respondents were unable to learn from previous errors and unable to detect their errors in estimate and recall. This error in prediction leads the investor to bear the risk above their accepted level which is harmful to their wealth.
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. PMID:25941868
Forecasts: uncertain, inaccurate and biased?
DEFF Research Database (Denmark)
Nicolaisen, Morten Skou; Ambrasaite, Inga; Salling, Kim Bang
2012-01-01
construction costs, which account for the majority of total project costs. Second are the forecasts of travel time savings, which account for the majority of total project benefits. The latter of these is, inter alia, determined by forecasts of travel demand, which we shall use as a proxy for the forecasting......Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts of...... accuracy of project benefits. This paper presents results from an on-going research project on uncertainties in transport project evaluation (UNITE) that find forecasts of demand to be not only uncertain, but at times also highly inaccurate and often displaying a concerning degree of bias. Demand for road...
Modeling confirmation bias and polarization
Del Vicario, Michela; Caldarelli, Guido; Stanley, H Eugene; Quattrociocchi, Walter
2016-01-01
Online users tend to select claims that adhere to their system of beliefs and to ignore dissenting information. Confirmation bias, indeed, plays a pivotal role in viral phenomena. Furthermore, the wide availability of content on the web fosters the aggregation of likeminded people where debates tend to enforce group polarization. Such a configuration might alter the public debate and thus the formation of the public opinion. In this paper we provide a mathematical model to study online social debates and the related polarization dynamics. We assume the basic updating rule of the Bounded Confidence Model (BCM) and we develop two variations a) the Rewire with Bounded Confidence Model (RBCM), in which discordant links are broken until convergence is reached; and b) the Unbounded Confidence Model, under which the interaction among discordant pairs of users is allowed even with a negative feedback, either with the rewiring step (RUCM) or without it (UCM). From numerical simulations we find that the new models (UCM...
Machtay; Glatstein
1998-01-01
have shown overall survivals superior to age-matched controls). It is fallacious and illogical to compare nonrandomized series of observation to those of aggressive therapy. In addition to the above problem, the use of DSS introduces another potential issue which we will call the bias of cause-of-death-interpretation. All statistical endpoints (e.g., response rates, local-regional control, freedom from brain metastases), except OS, are known to depend heavily on the methods used to define the endpoint and are often subject to significant interobserver variability. There is no reason to believe that this problem does not occasionally occur with respect to defining a death as due to the index cancer or to intercurrent disease, even though this issue has been poorly studied. In many oncologic situations-for example, metastatic lung cancer-this form of bias does not exist. In some situations, such as head and neck cancer, this could be an intermediate problem (Was that lethal chest tumor a second primary or a metastasis?.Would the fatal aspiration pneumonia have occurred if he still had a tongue?.And what about Mr. B. described above?). In some situations, particularly relatively "good prognosis" neoplasms, this could be a substantial problem, particularly if the adjudication of whether or not a death is cancer-related is performed solely by researchers who have an "interest" in demonstrating a good DSS. What we are most concerned about with this form of bias relates to recent series on observation, such as in early prostate cancer. It is interesting to note that although only 10% of the "observed" patients die from prostate cancer, many develop distant metastases by 10 years (approximately 40% among patients with intermediate grade tumors). Thus, it is implied that many prostate cancer metastases are usually not of themselves lethal, which is a misconception to anyone experienced in taking care of prostate cancer patients. This is inconsistent with U.S. studies of
A Simulation Platform for Quantifying Survival Bias
DEFF Research Database (Denmark)
Mayeda, Elizabeth Rose; Tchetgen Tchetgen, Eric J; Power, Melinda C;
2016-01-01
with the situation with no collider bias, the magnitude of bias was higher when exposure and an unmeasured determinant of cognitive decline interacted on the hazard ratio scale to influence mortality or when both exposure and rate of cognitive decline influenced mortality. Bias was, as expected, larger in high......-mortality situations. This simulation platform provides a flexible tool for evaluating biases in studies with high mortality, as is common in cognitive aging research.......Bias due to selective mortality is a potential concern in many studies and is especially relevant in cognitive aging research because cognitive impairment strongly predicts subsequent mortality. Biased estimation of the effect of an exposure on rate of cognitive decline can occur when mortality...
Professional Culture and Climate: Addressing Unconscious Bias
Knezek, Patricia
2016-10-01
Unconscious bias reflects expectations or stereotypes that influence our judgments of others (regardless of our own group). Everyone has unconscious biases. The end result of unconscious bias can be an accumulation of advantage or disadvantage that impacts the long term career success of individuals, depending on which biases they are subject to. In order to foster a professional culture and climate, being aware of these unconscious biases and mitigating against them is a first step. This is particularly important when judgements are needed, such as in cases for recruitment, choice of speakers for conferences, and even reviewing papers submitted for publication. This presentation will cover how unconscious bias manifests itself, what evidence exists to demonstrate it exists, and ways it can be addressed.
Biased random walks on multiplex networks
Battiston, Federico; Latora, Vito
2015-01-01
Biased random walks on complex networks are a particular type of walks whose motion is biased on properties of the destination node, such as its degree. In recent years they have been exploited to design efficient strategies to explore a network, for instance by constructing maximally mixing trajectories or by sampling homogeneously the nodes. In multiplex networks, the nodes are related through different types of links (layers or communication channels), and the presence of connections at different layers multiplies the number of possible paths in the graph. In this work we introduce biased random walks on multiplex networks and provide analytical solutions for their long-term properties such as the stationary distribution and the entropy rate. We focus on degree-biased walks and distinguish between two subclasses of random walks: extensive biased walks consider the properties of each node separately at each layer, intensive biased walks deal instead with intrinsically multiplex variables. We study the effec...
Shah, Nirvi
2011-01-01
America's 2.5 million Muslims make up less than 1 percent of the U.S. population, according to the Pew Research Center. Anecdotally, educators know that many Muslim students face discrimination. Unfortunately, no group or government agency keeps statistics on the subject. But some cases have warranted investigation by the U.S. Department of…
Childhood Obesity: Issues of Weight Bias
Washington, Reginald L.
2011-01-01
Although the effects of obesity on children's physical health are well documented, the social consequences of obesity are less well described and may not be addressed in intervention programs. Weight bias may take several forms. It may result in teasing and discrimination and may affect employment and educational opportunities. Health care providers may limit care of overweight or obese children. The media promote weight bias in multiple ways. Some parents are biased against their obese child...
BUSINESS LEADERSHIP BIASES: ANDROCENTRISM, ETHNOCENTRISM AND CHRONOCENTRISM
SOFICA Aurelian; NEGRUTA Adina
2012-01-01
The aim of the paper is to explore the unconscious biases that accompany the business leadership icons. The main objectives of the paper are: to look for evidence of leadership biases on ground of gender (androcentrism), ethnicity (ethnocentrism) and age (cronocentrism); to look for potential reasons behind the biases and for potential effects at the organizational and social level. The article confirms some of the evidence from various international empirical or theoretical studies, and prop...
Exponential Growth Bias and Financial Literacy
Almenberg, Johan; Gerdes, Christer
2011-01-01
The tendency to underestimate the future value of a variable growing at a constant rate, an example of exponential growth bias, has been linked to household financial decision making. We show that exponential growth bias and standard measures of financial literacy are negatively correlated in a representative sample of Swedish adults. Since financial literacy is linked to household decision making, our results indicate that examining the relationship between exponential growth bias and househ...
Voter Confirmation Bias and Electoral Accountability
Lockwood, Benjamin
2015-01-01
This paper considers the implications of an important cognitive bias in information processing, confirmation bias, in a political agency setting. In the baseline two-period case where only the politician’s actions are observable before the election, we show that when voters have this bias, it decreases pandering by the incumbent, and can raise voter welfare as a consequence. This result is robust in several directions, including to the case where the voter can also observe payoffs with some p...
Explorations in statistics: statistical facets of reproducibility.
Curran-Everett, Douglas
2016-06-01
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This eleventh installment of Explorations in Statistics explores statistical facets of reproducibility. If we obtain an experimental result that is scientifically meaningful and statistically unusual, we would like to know that our result reflects a general biological phenomenon that another researcher could reproduce if (s)he repeated our experiment. But more often than not, we may learn this researcher cannot replicate our result. The National Institutes of Health and the Federation of American Societies for Experimental Biology have created training modules and outlined strategies to help improve the reproducibility of research. These particular approaches are necessary, but they are not sufficient. The principles of hypothesis testing and estimation are inherent to the notion of reproducibility in science. If we want to improve the reproducibility of our research, then we need to rethink how we apply fundamental concepts of statistics to our science.
Purohit, Sudha G; Deshmukh, Shailaja R
2015-01-01
STATISTICS USING R will be useful at different levels, from an undergraduate course in statistics, through graduate courses in biological sciences, engineering, management and so on. The book introduces statistical terminology and defines it for the benefit of a novice. For a practicing statistician, it will serve as a guide to R language for statistical analysis. For a researcher, it is a dual guide, simultaneously explaining appropriate statistical methods for the problems at hand and indicating how these methods can be implemented using the R language. For a software developer, it is a guide in a variety of statistical methods for development of a suite of statistical procedures.
Weak coin flipping with small bias
Kerenidis, I; Kerenidis, Iordanis; Nayak, Ashwin
2002-01-01
This note presents a quantum protocol that demonstrates that_weak_ coin flipping with bias approximately 0.239, less than 1/4, is possible. A bias of 1/4 was the smallest known, and followed from the strong coin flipping protocol of [Ambainis 2001]. Protocols with yet smaller bias, approximately 0.207, have independently been discovered [Ambainis 2001, Spekkens and Rudolph 2002]. We also present an alternative strong coin flipping protocol with bias 1/4 with analysis simpler than that of [Ambainis 2001].
Detecting Gender Bias Through Test Item Analysis
González-Espada, Wilson J.
2009-03-01
Many physical science and physics instructors might not be trained in pedagogically appropriate test construction methods. This could lead to test items that do not measure what they are intended to measure. A subgroup of these items might show bias against some groups of students. This paper describes how the author became aware of potentially biased items against females in his examinations, which led to the exploration of fundamental issues related to item validity, gender bias, and differential item functioning, or DIF. A brief discussion of DIF in the context of university courses, as well as practical suggestions to detect possible gender-biased items, follows.
Memory biased random walk approach to synthetic clickstream generation
Antulov-Fantulin, Nino; Zlatic, Vinko; Grcar, Miha; Smuc, Tomislav
2012-01-01
Personalized recommender systems rely on personal usage data of each user in the system. However, privacy policies protecting users' rights prevent this data of being publicly available to a wider researcher audience. In this work, we propose a memory biased random walk model (MBRW) based on real clickstream graphs, as a generator of synthetic clickstreams that conform to statistical properties of the real clickstream data, while, at the same time, adhering to the privacy protection policies. We show that synthetic clickstreams can be used to learn recommender system models which achieve high recommender performance on real data and at the same time assuring that strong de-minimization guarantees are provided.
Effect of percent non-detects on estimation bias in censored distributions
Zhang, Z.; Lennox, W. C.; Panu, U. S.
2004-09-01
Uniqueness of the problem surrounding non-detects has been a concern alike to researchers and statisticians dealing with summary statistics while analyzing censored data. To incorporate non-detects in the estimation process, a simple substitution by the MDL (method detection limit) and the maximum likelihood estimation method are routinely implemented as standard methods by US-EPA laboratories. In situations where numerical standards are set at or near the MDL by regulatory agencies, it is prudent and important to closely investigate both the variability in test measurements and the estimation bias, because an inference based on biased estimates could entail significant liabilities. Variability is understood to be not only inevitable but also an inherent and integral part of any chemical analysis or test. In situations where regulatory agencies fail to account for the inherently present variability of test measurements, there is a need for regulated facilities to seek remedial action merely as a consequence of inadequate statistical procedure. This paper utilizes a mathematical approach to derive the bias functions and resulting bias curves are developed to investigate the censored samples from a variety of probability distributions such as normal, log-normal, gamma, and Gumbel distributions. Finally, the bias functions and bias curves are also compared to the results obtained by using Monte Carlo simulations.
Jak, S.; Oort, F.J.; Dolan, C. V.
2010-01-01
Restricted factor analysis can be used to investigate measurement bias. A prerequisite for the detection of measurement bias through factor analysis is the correct specification of the measurement model. We applied restricted factor analysis to two subtests of a Dutch cognitive ability test. These two examples serve to illustrate the relationship between multidimensionality and measurement bias. We conclude that measurement bias implies multidimensionality, whereas multidimensionality shows u...
System Model Bias Processing Approach for Regional Coordinated States Information Involved Filtering
Directory of Open Access Journals (Sweden)
Zebo Zhou
2016-01-01
Full Text Available In the Kalman filtering applications, the conventional dynamic model which connects the states information of two consecutive epochs by state transition matrix is usually predefined and assumed to be invariant. Aiming to improve the adaptability and accuracy of dynamic model, we propose multiple historical states involved filtering algorithm. An autoregressive model is used as the dynamic model which is subsequently combined with observation model for deriving the optimal window-recursive filter formulae in the sense of minimum mean square error principle. The corresponding test statistics characteristics of system residuals are discussed in details. The test statistics of regional predicted residuals are then constructed in a time-window for model bias testing with two hypotheses, that is, the null and alternative hypotheses. Based on the innovations test statistics, we develop a model bias processing procedure including bias detection, location identification, and state correction. Finally, the minimum detectable bias and bias-to-noise ratio are both computed for evaluating the internal and external reliability of overall system, respectively.
Ganichev, Sergey D.; Bel'Kov, Vasily V.; Tarasenko, Sergey A.; Danilov, Sergey N.; Giglberger, Stephan; Hoffmann, Christoph; Ivchenko, Eougenious L.; Weiss, Dieter; Wegscheider, Werner; Gerl, Christian; Schuh, Dieter; Stahl, Joachim; de Boeck, Jo; Borghs, Gustaaf; Prettl, Wilhelm
2006-09-01
The generation, manipulation and detection of spin-polarized electrons in low-dimensional semiconductors are at the heart of spintronics. Pure spin currents, that is, fluxes of magnetization without charge current, are quite attractive in this respect. A paradigmatic example is the spin Hall effect, where an electrical current drives a transverse spin current and causes a non-equilibrium spin accumulation observed near the sample boundary. Here we provide evidence for an another effect causing spin currents which is fundamentally different from the spin Hall effect. In contrast to the spin Hall effect, it does not require an electric current to flow: without bias the spin separation is achieved by spin-dependent scattering of electrons in media with suitable symmetry. We show, by free-carrier absorption of terahertz (THz) radiation, that spin currents flow in a wide range of temperatures. Moreover, the experimental results provide evidence that simple electron gas heating by any means is already sufficient to yield spin separation due to spin-dependent energy-relaxation processes.
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
A simple model for biased divertors
Energy Technology Data Exchange (ETDEWEB)
Lachambre, J.-L.; Quirion, B.; Gunn, J.; Boucher, C.; Stansfield, B.; Gauvreau, J.-L. [Centre canadien de fusion magnetique, 1804, boulevard Lionel-Boulet, Varennes, Quebec, J3X 1S1 (Canada)
1997-12-01
Ionization near the target plate is shown to play an important role in biasing experiments. Our previous SOL model, which calculates the induced radial electric field, is found to be inadequate to treat the new divertor geometry of TdeV. When recycling is included via the measured D{sub {alpha}} emission near the plate, the upgraded model correctly reproduces all the observed electric currents and fields during biasing in the new divertor configuration. A simple divertor model using this calculated field has been developed to simulate the evolution of the divertor ion and neutral parameters under the action of neutralization plate biasing. Using a 1D adiabatic fluid model for the divertor ions, a 1D convective representation for the SOL neutrals and a 0D calculation for the plenum pressure, this divertor model satisfactorily simulates most of the TdeV biasing experiments at all biasing voltages and all toroidal field directions at low line-averaged densities. The weaker agreement at high densities is largely a consequence of the crudeness of the general divertor physics rather than of the deficiency of the biasing physics implemented in the model. The model is finally used to explain the polarity asymmetries observed in divertor efficiencies during biasing, and to demonstrate that no mechanism other than plate current saturation is required to interpret the saturation of toroidal rotation observed in the SOL at large biasing voltages of either polarity. (author)
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...
EVIDENCE OF NATIONALISTIC BIAS IN MUAYTHAI
Directory of Open Access Journals (Sweden)
Tony D. Myers
2006-07-01
Full Text Available MuayThai is a combat sport with a growing international profile but limited research conducted into judging practices and processes. Problems with judging of other subjectively judged combat sports have caused controversy at major international tournaments that have resulted in changes to scoring methods. Nationalistic bias has been central to these problems and has been identified across a range of sports. The aim of this study was to examine nationalistic bias in MuayThai. Data were collected from the International Federation of MuayThai Amateur (IFMA World Championships held in Almaty, Kazakhstan September 2003 and comprised of tournament results from 70 A-class MuayThai bouts each judged by between five and nine judges. Bouts examined featured 62 competitors from 21 countries and 25 judges from 11 countries. Results suggested that nationalistic bias was evident. The bias observed equated to approximately one round difference between opposing judges over the course of a bout (a mean of 1.09 (SE=0.50 points difference between judges with opposing affilations. The number of neutral judges used meant that this level of bias generally did not influence the outcome of bouts. Future research should explore other ingroup biases, such as nearest neighbour bias and political bias as well as investigating the feasibility adopting an electronic scoring system
Racially Biased Policing: Determinants of Citizen Perceptions
Weitzer, Ronald; Tuch, Steven A.
2005-01-01
The current controversy surrounding racial profiling in America has focused renewed attention on the larger issue of racial bias by the police. Yet little is known about the extent of police racial bias and even less about public perceptions of the problem. This article analyzes recent national survey data on citizens' views of and reported…
A specific attentional bias in suicide attempters
Becker, E.S.; Strohbach, D.; Rinck, M.
1999-01-01
Selective attention in patients after an attempted suicide was investigated to find out whether a specific attentional bias for suicide-related materials exists and to clarify the possible role of emotions in the bias. Thirty-one patients who had previously attempted to commit suicide and 31 control
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...
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,...
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...
Estimating Sampling Selection Bias in Human Genetics: A Phenomenological Approach
Risso, Davide; Taglioli, Luca; De Iasio, Sergio; Gueresi, Paola; Alfani, Guido; Nelli, Sergio; Rossi, Paolo; Paoli, Giorgio; Tofanelli, Sergio
2015-01-01
This research is the first empirical attempt to calculate the various components of the hidden bias associated with the sampling strategies routinely-used in human genetics, with special reference to surname-based strategies. We reconstructed surname distributions of 26 Italian communities with different demographic features across the last six centuries (years 1447–2001). The degree of overlapping between "reference founding core" distributions and the distributions obtained from sampling the present day communities by probabilistic and selective methods was quantified under different conditions and models. When taking into account only one individual per surname (low kinship model), the average discrepancy was 59.5%, with a peak of 84% by random sampling. When multiple individuals per surname were considered (high kinship model), the discrepancy decreased by 8–30% at the cost of a larger variance. Criteria aimed at maximizing locally-spread patrilineages and long-term residency appeared to be affected by recent gene flows much more than expected. Selection of the more frequent family names following low kinship criteria proved to be a suitable approach only for historically stable communities. In any other case true random sampling, despite its high variance, did not return more biased estimates than other selective methods. Our results indicate that the sampling of individuals bearing historically documented surnames (founders' method) should be applied, especially when studying the male-specific genome, to prevent an over-stratification of ancient and recent genetic components that heavily biases inferences and statistics. PMID:26452043
Modelling large-scale halo bias using the bispectrum
Pollack, Jennifer E; Porciani, Cristiano
2011-01-01
We study the relation between the halo and matter density fields -- commonly termed bias -- in the LCDM framework. In particular, we examine the local model of biasing at quadratic order in matter density. This model is characterized by parameters b_1 and b_2. Using an ensemble of N-body simulations, we apply several statistical methods to estimate the parameters. We measure halo and matter fluctuations smoothed on various scales and find that the parameters vary with smoothing scale. We argue that, for real-space measurements, owing to the mixing of wavemodes, no scale can be found for which the parameters are independent of smoothing. However, this is not the case in Fourier space. We measure halo power spectra and construct estimates for an effective large-scale bias. We measure the configuration dependence of the halo bispectra B_hhh and reduced bispectra Q_hhh for very large-scale k-space triangles. From this we constrain b_1 and b_2. Using the lowest-order perturbation theory, we find that for B_hhh the...
Wind models for the NSTS ascent trajectory biasing for wind load alleviation
Smith, O. E.; Adelfang, S. I.; Batts, G. W.
1990-01-01
New concepts are presented for aerospace vehicle ascent wind profile biasing. The purpose for wind biasing the ascent trajectory is to provide ascent wind loads relief and thus decrease the probability for launch delays due to wind loads exceeding critical limits. Wind biasing trajectories to the the profile of monthly mean winds have been widely used for this purpose. The wind profile models presented give additional alternatives for wind biased trajectories. They are derived from the properties of the bivariate normal probability function using the available wind statistical parameters for the launch site. The analytical expressions are presented to permit generalizations. Specific examples are given to illustrate the procedures. The wind profile models can be used to establish the ascent trajectory steering commands to guide the vehicle through the first stage. For the National Space Transportation System (NSTS) program these steering commands are called I-loads.
Expressing precision and bias in calorimetry
Energy Technology Data Exchange (ETDEWEB)
Hauck, Danielle K [Los Alamos National Laboratory; Croft, Stephen [Los Alamos National Laboratory; Bracken, David S [Los Alamos National Laboratory
2010-01-01
The calibration and calibration verification of a nuclear calorimeter represents a substantial investment of time in part because a single calorimeter measurement takes of the order of 2 to 24h to complete. The time to complete a measurement generally increases with the size of the calorimeter measurement well. It is therefore important to plan the sequence of measurements rather carefully so as to cover the dynamic range and achieve the required accuracy within a reasonable time frame. This work will discuss how calibrations and their verification has been done in the past and what we consider to be good general practice in this regard. A proposed approach to calibration and calibration verification is presented which, in the final analysis, makes use of all the available data - both calibration and verification collectively - in order to obtain the best (in a best fit sense) possible calibration. The combination of sample variance and percent recovery are traditionally taken as sufficient to capture the random (precision) and systematic (bias) contributions to the uncertainty in a calorimetric assay. These terms have been defined as well as formulated for a basic calibration. It has been tradition to assume that sensitivity is a linear function of power. However, the availability of computer power and statistical packages should be utilized to fit the response function as accurately as possible using whatever functions are deemed most suitable. Allowing for more flexibility in the response function fit will enable the calibration to be updated according to the results from regular validation measurements through the year. In a companion paper to be published elsewhere we plan to discuss alternative fitting functions.
Composite biasing in Monte Carlo radiative transfer
Baes, Maarten; Lunttila, Tuomas; Bianchi, Simone; Camps, Peter; Juvela, Mika; Kuiper, Rolf
2016-01-01
Biasing or importance sampling is a powerful technique in Monte Carlo radiative transfer, and can be applied in different forms to increase the accuracy and efficiency of simulations. One of the drawbacks of the use of biasing is the potential introduction of large weight factors. We discuss a general strategy, composite biasing, to suppress the appearance of large weight factors. We use this composite biasing approach for two different problems faced by current state-of-the-art Monte Carlo radiative transfer codes: the generation of photon packages from multiple components, and the penetration of radiation through high optical depth barriers. In both cases, the implementation of the relevant algorithms is trivial and does not interfere with any other optimisation techniques. Through simple test models, we demonstrate the general applicability, accuracy and efficiency of the composite biasing approach. In particular, for the penetration of high optical depths, the gain in efficiency is spectacular for the spe...
Galaxy Bias in Quintessence Cosmological Models
Basilakos, S
2003-01-01
We derive the evolution of the linear bias factor, $b(z)$, in cosmological models driven by an exotic fluid with an equation of state: $p_{x}=w\\rho_{x}$, where $-1\\le w<0$ (quintessence). Our aim is to put constrains on different cosmological and biasing models by combining the recent observational clustering results of optical ({\\em 2dF}) galaxies (Hawkings et al.) with those predicted by the models. We find that our bias model when fitted to the {\\em 2dF} clustering results predicts different bias evolution for different values of $w$. The models that provide the weak biasing ($b_{\\circ} \\sim 1.1$) of optical galaxies found in many recent observational studies are flat, $\\Omega_{\\rm m}=0.3$ with $w\\le -0.9$. These models however, predict a weak redshift evolution of $b(z)$, not corroborated by N-body simulations.
Heterozygosity and extra-pair paternity: biased tests result from the use of shared markers.
Wetzel, Daniel P; Westneat, David F
2009-05-01
Recent studies of extra-pair paternity have found support for the idea that heterozygous males have an advantage in siring offspring. Most studies use DNA microsatellite loci to determine paternity and then use the same loci to estimate individual heterozygosity. However, because the likelihood of detecting extra-pair offspring depends on the combinations of parental alleles, it is possible that biases arise from particular allele combinations. This might produce false support for the influence of heterozygosity on mating behaviour. We used a simulation model to assess how large this bias might be. We found two sources of bias. First, we found a bias in the null hypothesis of a simple statistical test commonly used to test several predictions of the heterozygosity hypothesis. The use of randomization tests could eliminate this bias. Second, we found that using the same loci for both paternity and heterozygosity can cause an increase in results supporting the heterozygosity hypothesis when no effect of heterozygosity actually exists. This bias is reduced through the use of more markers with higher levels of polymorphism and heterozygosity, but can be eliminated entirely by using a separate set of markers to determine paternity and assess heterozygosity. The two sources of bias reduce evidence favouring the heterozygosity hypothesis, but do not negate all of the studies that support it. We suggest that further studies of heterozygosity and extra-pair paternity are important and likely to be informative, but our recommendations should be incorporated by researchers to improve the reliability of their conclusions.
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 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...
Cancer Statistics: Pancreas Cancer
... qnad9A-rfcw?rel=0 SEER Stat Fact Sheets: Pancreas Cancer Expand All Collapse All Statistics at a ... 5 Years Or More after Being Diagnosed with Pancreas Cancer? Relative survival statistics compare the survival of ...
... About Blood > Blood Facts and Statistics Printable Version Blood Facts and Statistics Facts about blood needs Facts ... about American Red Cross Blood Services Facts about blood needs Every two seconds someone in the U.S. ...
Overweight and Obesity Statistics
... the full list of resources . Overweight and Obesity Statistics Page Content About Overweight and Obesity Prevalence of ... adults age 20 and older [ Top ] Physical Activity Statistics Adults Research Findings Research suggests that staying active ...
... Research AMIGAS Fighting Cervical Cancer Worldwide Stay Informed Statistics for Other Kinds of Cancer Breast Cervical Colorectal ( ... Skin Vaginal and Vulvar Cancer Home Uterine Cancer Statistics Language: English Español (Spanish) Recommend on Facebook Tweet ...
... population data for older age groups are available. Statistics at a Glance Show More At a Glance ... with ovarian cancer in the United States. Survival Statistics Show More How Many People Survive 5 Years ...
... population data for older age groups are available. Statistics at a Glance Show More At a Glance ... living with leukemia in the United States. Survival Statistics Show More How Many People Survive 5 Years ...
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...
Software for Spatial Statistics
Directory of Open Access Journals (Sweden)
Edzer Pebesma
2015-02-01
Full Text Available We give an overview of the papers published in this special issue on spatial statistics, of the Journal of Statistical Software. 21 papers address issues covering visualization (micromaps, links to Google Maps or Google Earth, point pattern analysis, geostatistics, analysis of areal aggregated or lattice data, spatio-temporal statistics, Bayesian spatial statistics, and Laplace approximations. We also point to earlier publications in this journal on the same topic.
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
Mathematical statistics with applications
Ramachandran, KM
2009-01-01
Mathematical Statistics with Applications provides a calculus-based theoretical introduction to mathematical statistics while emphasizing interdisciplinary applications as well as exposure to modern statistical computational and simulation concepts that are not covered in other textbooks. Includes the Jackknife, Bootstrap methods, the EM algorithms and Markov chain Monte Carlo methods. Prior probability or statistics knowledge is not required.* Step-by-step procedure to solve real problems, making the topic more accessible* Exercises blend theory and modern applications*
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…
Computing and Introductory Statistics
Kaplan, Daniel
2007-01-01
Much of the computing that students do in introductory statistics courses is based on techniques that were developed before computing became inexpensive and ubiquitous. Now that computing is readily available to all students, instructors can change the way we teach statistical concepts. This article describes computational ideas that can support teaching George Cobb's Three Rs of statistical inference: Randomize, Repeat, Reject.
What to do with the upward bias in R(2) : A comment
Snijders, TAB
1996-01-01
A recent article by Huberty (1994) discusses significance testing of R(2) in linear regression and the definition of a corresponding effect size index. It recommends an adjustment to the standard null hypothesis, p(2) = 0, in order to adjust for an upward bias in the statistic R(2). This note sugges
Explorations in statistics: statistical facets of reproducibility.
Curran-Everett, Douglas
2016-06-01
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This eleventh installment of Explorations in Statistics explores statistical facets of reproducibility. If we obtain an experimental result that is scientifically meaningful and statistically unusual, we would like to know that our result reflects a general biological phenomenon that another researcher could reproduce if (s)he repeated our experiment. But more often than not, we may learn this researcher cannot replicate our result. The National Institutes of Health and the Federation of American Societies for Experimental Biology have created training modules and outlined strategies to help improve the reproducibility of research. These particular approaches are necessary, but they are not sufficient. The principles of hypothesis testing and estimation are inherent to the notion of reproducibility in science. If we want to improve the reproducibility of our research, then we need to rethink how we apply fundamental concepts of statistics to our science. PMID:27231259
Dopaminergic genes predict individual differences in susceptibility to confirmation bias.
Doll, Bradley B; Hutchison, Kent E; Frank, Michael J
2011-04-20
The striatum is critical for the incremental learning of values associated with behavioral actions. The prefrontal cortex (PFC) represents abstract rules and explicit contingencies to support rapid behavioral adaptation in the absence of cumulative experience. Here we test two alternative models of the interaction between these systems, and individual differences thereof, when human subjects are instructed with prior information about reward contingencies that may or may not be accurate. Behaviorally, subjects are overly influenced by prior instructions, at the expense of learning true reinforcement statistics. Computational analysis found that this pattern of data is best accounted for by a confirmation bias mechanism in which prior beliefs--putatively represented in PFC--influence the learning that occurs in the striatum such that reinforcement statistics are distorted. We assessed genetic variants affecting prefrontal and striatal dopaminergic neurotransmission. A polymorphism in the COMT gene (rs4680), associated with prefrontal dopaminergic function, was predictive of the degree to which participants persisted in responding in accordance with prior instructions even as evidence against their veracity accumulated. Polymorphisms in genes associated with striatal dopamine function (DARPP-32, rs907094, and DRD2, rs6277) were predictive of learning from positive and negative outcomes. Notably, these same variants were predictive of the degree to which such learning was overly inflated or neglected when outcomes are consistent or inconsistent with prior instructions. These findings indicate dissociable neurocomputational and genetic mechanisms by which initial biases are strengthened by experience. PMID:21508242
The ergodicity bias in the observed galaxy distribution
Energy Technology Data Exchange (ETDEWEB)
Pan, Jun [The Purple Mountain Observatory, 2 West Beijing Road, Nanjing 210008 (China); Zhang, Pengjie, E-mail: jpan@pmo.ac.cn, E-mail: pjzhang@shao.ac.cn [Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, 80 Nandan Road, Shanghai, 200030 (China)
2010-08-01
The spatial distribution of galaxies we observed is subject to the given condition that we, human beings are sitting right in a galaxy — the Milky Way. Thus the ergodicity assumption is questionable in interpretation of the observed galaxy distribution. The resultant difference between observed statistics (volume average) and the true cosmic value (ensemble average) is termed as the ergodicity bias. We perform explicit numerical investigation of the effect for a set of galaxy survey depths and near-end distance cuts. It is found that the ergodicity bias in observed two- and three-point correlation functions in most cases is insignificant for modern analysis of samples from galaxy surveys and thus close a loophole in precision cosmology. However, it may become non-negligible in certain circumstances, such as those applications involving three-point correlation function at large scales of local galaxy samples. Thus one is reminded to take extra care in galaxy sample construction and interpretation of the statistics of the sample, especially when the characteristic redshift is low.
Systematic bias in NMR diffusion measurements on polydisperse systems.
Zhou, Xiaoyue; Xu, Kaipin; Zhang, Shanmin
2015-03-01
Least-squares fitting of the Stejskal-Tanner equation is a routine process in the measurement of molecular diffusion coefficient (MDC) using Nuclear Magnetic Resonance (NMR) Spectroscopy. It is simple and elegant. However, a bias of the MDC is noticed when the system is polydispersed. This is due to improper accounts of the diffusion coefficient distribution. Eventually, it leads to a discrepancy between the observed MDC and the statistical mean value of the distribution. To reveal the discrepancy, an analytical solution is derived when the diffusion data is taken a logarithmic linearization. Computer simulation is also applied to obtain a non-linear regression result. For a Gaussian distribution of the MDCs, the bias is proportional to the square of the distribution width (linear regression), but it is also inversely proportional to the statistical mean value of the distribution (non-linear regression). This indicates that the MDC derived from Stejskal-Tanner equation only holds well for narrow distribution of MDCs. Otherwise, molecular radius derived from the Stokes-Einstein equation needs to be reconsidered due to the incorrect estimation of the MDC.
Weight Bias in University Health Professions Students.
Blanton, Cynthia; Brooks, Jennifer K; McKnight, Laura
2016-01-01
Negative attitudes toward people with high body weight have been documented in pre-professional health students, prompting concern that such feelings may manifest as poor patient care in professional practice. This study assessed weight bias in university students in the non-physician health professions. A convenience sample of 206 students completed an online survey composed of a validated 14-item scale (1-5 lowest to highest weight bias) and questions regarding personal experiences of weight bias. Respondents were grouped by discipline within graduate and undergraduate levels. Weight bias was present in a majority of respondents. Overall, the percentage of responses indicative of weight bias was 92.7%. The mean total score was 3.65. ± 0.52, and the rating exceeded 3 for all 14 scale descriptors of high-weight people. In graduate students, discipline had a significant main effect on total score (p=0.01), with lower scores in dietetics (3.17 ± 0.46) vs audiology/sign language/speech language pathology (3.84 ± 0.41) and physician assistant students (3.78 ± 0.51; pweight bias is prevalent in health professions students at a mountain west university. Well-controlled studies that track students into professional practice would help determine whether bias-reduction interventions in college improve provider behaviors and clinical outcomes. PMID:27585618
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
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
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
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.
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
Statistics Essentials For Dummies
Rumsey, Deborah
2010-01-01
Statistics Essentials For Dummies not only provides students enrolled in Statistics I with an excellent high-level overview of key concepts, but it also serves as a reference or refresher for students in upper-level statistics courses. Free of review and ramp-up material, Statistics Essentials For Dummies sticks to the point, with content focused on key course topics only. It provides discrete explanations of essential concepts taught in a typical first semester college-level statistics course, from odds and error margins to confidence intervals and conclusions. This guide is also a perfect re
Estimation and inferential statistics
Sahu, Pradip Kumar; Das, Ajit Kumar
2015-01-01
This book focuses on the meaning of statistical inference and estimation. Statistical inference is concerned with the problems of estimation of population parameters and testing hypotheses. Primarily aimed at undergraduate and postgraduate students of statistics, the book is also useful to professionals and researchers in statistical, medical, social and other disciplines. It discusses current methodological techniques used in statistics and related interdisciplinary areas. Every concept is supported with relevant research examples to help readers to find the most suitable application. Statistical tools have been presented by using real-life examples, removing the “fear factor” usually associated with this complex subject. The book will help readers to discover diverse perspectives of statistical theory followed by relevant worked-out examples. Keeping in mind the needs of readers, as well as constantly changing scenarios, the material is presented in an easy-to-understand form.
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.
Reference List About Implicit and Unconscious Bias
DEFF Research Database (Denmark)
Munar, Ana Maria; Villeseche, Florence; Weidemann, Cecilie Dam
and knowledge base on diversity- and inclusion-related topics. An implicit and/or unconscious bias is a bias that we are unaware of and is therefore expressed unwillingly and unknowingly. As recent studies on implicit bias indicate “we now know that the operation of prejudice and stereotyping in social judgment...... to publications accessible through the CBS library website and/or specifications of where and how to access each publication. In addition, as part of this effort and in line with the task list of the Council for Diversity and Inclusion, the report “Gender and Leadership Practices at Copenhagen Business School...
Forecast Bias Correction: A Second Order Method
Crowell, Sean
2010-01-01
The difference between a model forecast and actual observations is called forecast bias. This bias is due to either incomplete model assumptions and/or poorly known parameter values and initial/boundary conditions. In this paper we discuss a method for estimating corrections to parameters and initial conditions that would account for the forecast bias. A set of simple experiments with the logistic ordinary differential equation is performed using an iterative version of a first order version of our method to compare with the second order version of the method.
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 Statistica
Escaping RGBland: Selecting Colors for Statistical Graphics
Zeileis, Achim; Hornik, Kurt; Murrell, Paul
2007-01-01
Statistical graphics are often augmented by the use of color coding information contained in some variable. When this involves the shading of areas (and not only points or lines) - e.g., as in bar plots, pie charts, mosaic displays or heatmaps - it is important that the colors are perceptually based and do not introduce optical illusions or systematic bias. Here, we discuss how the perceptually-based Hue-Chroma-Luminance (HCL) color space can be used for deriving suitable color palettes for c...
Choosing Color Palettes for Statistical Graphics
Zeileis, Achim; Hornik, Kurt
2006-01-01
Statistical graphics are often augmented by the use of color coding information contained in some variable. When this involves the shading of areas (and not only points or lines) - e.g., as in bar plots, pie charts, mosaic displays or heatmaps - it is important that the colors are perceptually based and do not introduce optical illusions or systematic bias. Here, we discuss how the perceptually-based Hue-Chroma-Luminance (HCL) color space can be used for deriving suitable color palettes for c...
Accounting for Unobservable Exposure Time Bias Wh...
U.S. Department of Health & Human Services — Accounting for Unobservable Exposure Time Bias When Using Medicare Prescription Drug Data Unobservable exposure time is common among Medicare Part D beneficiaries,...
Bootstrap bias-adjusted GMM estimators
Ramalho, Joaquim J.S.
2005-01-01
The ability of six alternative bootstrap methods to reduce the bias of GMM parameter estimates is examined in an instrumental variable framework using Monte Carlo analysis. Promising results were found for the two bootstrap estimators suggested in the paper.
Time Series Properties of Expectation Biases
Kinari, Yusuke
2011-01-01
This study exammes time senes properties of expectation biases usmg a highfrequency survey on stock price forecasts, which required participants to forecast the Nikkei 225 over three forecasting horizons: one day, one week, and one month ahead. Constructing proxies for overconfidence and optimism as the expectation biases, this study shows that overconfidence is likely to remain stable over time while optimism is not. Moreover, a relationship exists between optimism and stock price movement, ...
Biased liquid crystal photonic bandgap fiber
DEFF Research Database (Denmark)
Weirich, Johannes; Lægsgaard, Jesper; Alkeskjold, Thomas Tanggaard;
2008-01-01
We simulate the director structure of all capillaries in a biased photonic crystal fiber infiltrated with liquid crystals. Various mode simulations for different capillaries show the necessity to consider the entire structure.......We simulate the director structure of all capillaries in a biased photonic crystal fiber infiltrated with liquid crystals. Various mode simulations for different capillaries show the necessity to consider the entire structure....
Constraints on Assembly Bias from Galaxy Clustering
Zentner, Andrew R.; Hearin, Andrew; Bosch, Frank C. van den; Lange, Johannes U.; Villarreal, Antonio
2016-01-01
We constrain the newly-introduced decorated Halo Occupation Distribution (HOD) model using SDSS DR7 measurements of projected galaxy clustering or r-band luminosity threshold samples. The decorated HOD is a model for the galaxy-halo connection that augments the HOD by allowing for the possibility of galaxy assembly bias: galaxy luminosity may be correlated with dark matter halo properties besides mass, Mvir. We demonstrate that it is not possible to rule out galaxy assembly bias using DR7 mea...
Local Bias and Stock Market Conditions
Giannetti, Mariassunta; Laeven, Luc
2012-01-01
We show that the local bias in U.S. mutual fund portfolios varies significantly over time and is more pronounced at times of heightened market uncertainty, such as during financial crises. Similarly, the local bias is less pronounced in periods when market sentiment is strong. These results do not depend on past fund performance or fund inflows during good times. Additionally, we do not find that fund managers earn superior returns on local stocks during periods of heightened market uncertain...
Spending Biased Legislators - Discipline Through Disagreement
Facundo Piguillem; Alessandro Riboni
2013-01-01
This paper studies politicians who have a present-bias for spending; they want to increase current spending and procrastinate spending cuts. We argue that legislators' bias is more severe in economies with low institutional quality. We show that disagreement in legislatures leads to policy persistence and that this attenuates the temptation to overspend. Depending on the environment, legislators' decisions to be fiscally responsible may either complement or substitute other legislator's decis...
Clustering coefficient without degree correlations biases
Soffer, Sara Nadiv; Vazquez, Alexei
2004-01-01
The clustering coefficient quantifies how well connected are the neighbors of a vertex in a graph. In real networks it decreases with the vertex degree, which has been taken as a signature of the network hierarchical structure. Here we show that this signature of hierarchical structure is a consequence of degree correlation biases in the clustering coefficient definition. We introduce a new definition in which the degree correlation biases are filtered out, and provide evidence that in real n...
The Local Bias of Individual Investors
Ning Zhu
2002-01-01
This study investigates individual investors' bias towards nearby companies. Using data from a large U.S. discount brokerage, we find that individual investors tend to invest in companies closer to them relative to the market portfolio. Unlike Coval and Moskowitz's (1999) findings on institutional investors, however, we find that advantageous information cannot explain individual investors' local bias. Accounting numbers and information asymmetry matter less to individual investors' local bia...
Resolving Bias in Laser Ablation Geochronology
Bowring, James; Horstwood, Matthew; Gehrels, George
2013-06-01
Increasingly, scientific investigations requiring geochronology utilize laser ablation (LA)-inductively coupled plasma mass spectrometry (ICPMS), taking advantage of the efficiency and throughput possible for uranium-thorium-lead (U-Th-Pb) dating. A number of biases exist when comparing data among laboratories and an ongoing community-based effort is working to resolve and eliminate these biases to improve the accuracy of scientific interpretation based on these data.
Gaidos, Eric
2012-01-01
Statistical analyses of large surveys for transiting planets such as the Kepler mission must account for systematic errors and biases. Transit detection depends not only on the planet's radius and orbital period, but also on host star properties. Thus, a sample of stars with transiting planets may not accurately represent the target population. Moreover, targets are selected using criteria such as a limiting apparent magnitude. These selection effects, combined with uncertainties in stellar radius, lead to biases in the properties of transiting planets and their host stars. We quantify possible biases in the Kepler survey. First, Eddington bias produced by a steep planet radius distribution and uncertainties in stellar radius results in a 15-20% overestimate of planet occurrence. Second, the magnitude limit of the Kepler target catalog induces Malmquist bias towards large, more luminous stars and underestimation of the radii of about one third of candidate planets, especially those larger than Neptune. Third,...
Spatial Statistical Data Fusion (SSDF)
Braverman, Amy J.; Nguyen, Hai M.; Cressie, Noel
2013-01-01
As remote sensing for scientific purposes has transitioned from an experimental technology to an operational one, the selection of instruments has become more coordinated, so that the scientific community can exploit complementary measurements. However, tech nological and scientific heterogeneity across devices means that the statistical characteristics of the data they collect are different. The challenge addressed here is how to combine heterogeneous remote sensing data sets in a way that yields optimal statistical estimates of the underlying geophysical field, and provides rigorous uncertainty measures for those estimates. Different remote sensing data sets may have different spatial resolutions, different measurement error biases and variances, and other disparate characteristics. A state-of-the-art spatial statistical model was used to relate the true, but not directly observed, geophysical field to noisy, spatial aggregates observed by remote sensing instruments. The spatial covariances of the true field and the covariances of the true field with the observations were modeled. The observations are spatial averages of the true field values, over pixels, with different measurement noise superimposed. A kriging framework is used to infer optimal (minimum mean squared error and unbiased) estimates of the true field at point locations from pixel-level, noisy observations. A key feature of the spatial statistical model is the spatial mixed effects model that underlies it. The approach models the spatial covariance function of the underlying field using linear combinations of basis functions of fixed size. Approaches based on kriging require the inversion of very large spatial covariance matrices, and this is usually done by making simplifying assumptions about spatial covariance structure that simply do not hold for geophysical variables. In contrast, this method does not require these assumptions, and is also computationally much faster. This method is
Optimization techniques in statistics
Rustagi, Jagdish S
1994-01-01
Statistics help guide us to optimal decisions under uncertainty. A large variety of statistical problems are essentially solutions to optimization problems. The mathematical techniques of optimization are fundamentalto statistical theory and practice. In this book, Jagdish Rustagi provides full-spectrum coverage of these methods, ranging from classical optimization and Lagrange multipliers, to numerical techniques using gradients or direct search, to linear, nonlinear, and dynamic programming using the Kuhn-Tucker conditions or the Pontryagin maximal principle. Variational methods and optimiza
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
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
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
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.
Mathematical statistics with applications
Wackerly, Dennis D; Scheaffer, Richard L
2008-01-01
In their bestselling MATHEMATICAL STATISTICS WITH APPLICATIONS, premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps you discover the nature of statistics and understand its essential role in scientific research.
Rosenbaum, Paul R.
1991-01-01
Statistics or functions are discussed that measure agreement between certain types of partially ordered data. These poset statistics are a generalization of two familiar classes of functions: the arrangement increasing functions and the decreasing reflection functions; those functions measure agreement between linearly ordered data. Specifically, the statistics in question are functions $h(\\mathbf{X}_1, \\mathbf{X}_2)$ of two matrix arguments, each having $N$ rows and they measure the agreemen...
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
Bradley, Robert K.; Adam Roberts; Michael Smoot; Sudeep Juvekar; Jaeyoung Do; Colin Dewey; Ian Holmes; Lior Pachter
2009-01-01
We describe a new program for the alignment of multiple biological sequences that is both statistically motivated and fast enough for problem sizes that arise in practice. Our Fast Statistical Alignment program is based on pair hidden Markov models which approximate an insertion/deletion process on a tree and uses a sequence annealing algorithm to combine the posterior probabilities estimated from these models into a multiple alignment. FSA uses its explicit statistical model to produce multi...
Statistical Methods for Astronomy
Feigelson, Eric D.; Babu, G. Jogesh
2012-01-01
This review outlines concepts of mathematical statistics, elements of probability theory, hypothesis tests and point estimation for use in the analysis of modern astronomical data. Least squares, maximum likelihood, and Bayesian approaches to statistical inference are treated. Resampling methods, particularly the bootstrap, provide valuable procedures when distributions functions of statistics are not known. Several approaches to model selection and good- ness of fit are considered. Applied s...
Constraints on Assembly Bias from Galaxy Clustering
Zentner, Andrew R; Bosch, Frank C van den; Lange, Johannes U; Villarreal, Antonio
2016-01-01
We constrain the newly-introduced decorated Halo Occupation Distribution (HOD) model using SDSS DR7 measurements of projected galaxy clustering or r-band luminosity threshold samples. The decorated HOD is a model for the galaxy-halo connection that augments the HOD by allowing for the possibility of galaxy assembly bias: galaxy luminosity may be correlated with dark matter halo properties besides mass, Mvir. We demonstrate that it is not possible to rule out galaxy assembly bias using DR7 measurements of galaxy clustering alone. Moreover, galaxy samples with Mr < -20 and Mr < -20.5 favor strong central galaxy assembly bias. These samples prefer scenarios in which high-concentration are more likely to host a central galaxy relative to low-concentration halos of the same mass. We exclude zero assembly bias with high significance for these samples. Satellite galaxy assembly bias is significant for the faintest sample, Mr < -19. We find no evidence for assembly bias in the Mr < -21 sample. Assembly bi...
Ariwahjoedi, Seramika; Kosasih, Jusak Sali; Rovelli, Carlo; Zen, Freddy Permana
2016-01-01
Following our earlier work, we construct statistical discrete geometry by applying statistical mechanics to discrete (Regge) gravity. We propose a coarse-graining method for discrete geometry under the assumptions of atomism and background independence. To maintain these assumptions, restrictions are given to the theory by introducing cut-offs, both in ultraviolet and infrared regime. Having a well-defined statistical picture of discrete Regge geometry, we take the infinite degrees of freedom (large n) limit. We argue that the correct limit consistent with the restrictions and the background independence concept is not the continuum limit of statistical mechanics, but the thermodynamical limit.
Annual Statistical Supplement, 2014
Social Security Administration — The Annual Statistical Supplement, 2014 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
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
Paul, Rourab; Dey, Hemanta; Chakrabrti, Amlan; Ghosh, Ranjan
2016-01-01
The NIST Statistical Test Suite has 15 tests. The principal strategy of the NIST Statistical Test Suite is to judge statistical randomness property of random bit generating algorithms. Based on 300 to 500 different keys, the algorithm generates a series of even number of different long random sequences of n bits, n varying between 13 and 15 lacs, each of which is tested by the 15 tests. Each test has a specific statistic parameter for bit sequences under the assumption of randomness and calcu...
Annual Statistical Supplement, 2015
Social Security Administration — The Annual Statistical Supplement, 2015 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Record Statistics and Dynamics
DEFF Research Database (Denmark)
Sibani, Paolo; Jensen, Henrik J.
2009-01-01
The term record statistics covers the statistical properties of records within an ordered series of numerical data obtained from observations or measurements. A record within such series is simply a value larger (or smaller) than all preceding values. The mathematical properties of records strongly...... fluctuations of e. g. the energy are able to push the system past some sort of ‘edge of stability’, inducing irreversible configurational changes, whose statistics then closely follows the statistics of record fluctuations....
Schieve, William C.; Horwitz, Lawrence P.
2009-04-01
1. Foundations of quantum statistical mechanics; 2. Elementary examples; 3. Quantum statistical master equation; 4. Quantum kinetic equations; 5. Quantum irreversibility; 6. Entropy and dissipation: the microscopic theory; 7. Global equilibrium: thermostatics and the microcanonical ensemble; 8. Bose-Einstein ideal gas condensation; 9. Scaling, renormalization and the Ising model; 10. Relativistic covariant statistical mechanics of many particles; 11. Quantum optics and damping; 12. Entanglements; 13. Quantum measurement and irreversibility; 14. Quantum Langevin equation: quantum Brownian motion; 15. Linear response: fluctuation and dissipation theorems; 16. Time dependent quantum Green's functions; 17. Decay scattering; 18. Quantum statistical mechanics, extended; 19. Quantum transport with tunneling and reservoir ballistic transport; 20. Black hole thermodynamics; Appendix; Index.
Kanji, Gopal K
2006-01-01
This expanded and updated Third Edition of Gopal K. Kanji's best-selling resource on statistical tests covers all the most commonly used tests with information on how to calculate and interpret results with simple datasets. Each entry begins with a short summary statement about the test's purpose, and contains details of the test objective, the limitations (or assumptions) involved, a brief outline of the method, a worked example, and the numerical calculation. 100 Statistical Tests, Third Edition is the one indispensable guide for users of statistical materials and consumers of statistical information at all levels and across all disciplines.
Annual Statistical Supplement, 2010
Social Security Administration — The Annual Statistical Supplement, 2010 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2000
Social Security Administration — The Annual Statistical Supplement, 2000 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2004
Social Security Administration — The Annual Statistical Supplement, 2004 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2001
Social Security Administration — The Annual Statistical Supplement, 2001 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2003
Social Security Administration — The Annual Statistical Supplement, 2003 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2005
Social Security Administration — The Annual Statistical Supplement, 2005 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2007
Social Security Administration — The Annual Statistical Supplement, 2007 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2008
Social Security Administration — The Annual Statistical Supplement, 2008 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2009
Social Security Administration — The Annual Statistical Supplement, 2009 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
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...
Annual Statistical Supplement, 2006
Social Security Administration — The Annual Statistical Supplement, 2006 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2011
Social Security Administration — The Annual Statistical Supplement, 2011 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
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
Bulmer, M G
1979-01-01
There are many textbooks which describe current methods of statistical analysis, while neglecting related theory. There are equally many advanced textbooks which delve into the far reaches of statistical theory, while bypassing practical applications. But between these two approaches is an unfilled gap, in which theory and practice merge at an intermediate level. Professor M. G. Bulmer's Principles of Statistics, originally published in 1965, was created to fill that need. The new, corrected Dover edition of Principles of Statistics makes this invaluable mid-level text available once again fo
Sleep-related attentional bias in insomnia: A state-of-the-science review.
Harris, Kamelia; Spiegelhalder, Kai; Espie, Colin A; MacMahon, Kenneth M A; Woods, Heather Cleland; Kyle, Simon D
2015-12-01
Prominent models of insomnia posit that sleep-related attentional bias plays an important role in the development and maintenance of insomnia. Here we conduct the first systematic review of the sleep-related attentional bias construct, indexed through reaction time-based experimental tasks. Literature search identified 13 studies that met pre-defined inclusion/exclusion criteria. Included studies involved between-group comparisons (poor sleepers versus controls), as well as sleep manipulations and correlational investigations with healthy sleepers. For studies involving comparisons between poor sleepers and healthy controls, effect size estimates were computed for task-relevant dependent variables. Six of the nine studies comparing poor sleepers and controls revealed statistically significant group differences in support of a differential sleep-related attentional bias (medium-to-large effect sizes), with flicker, dot-probe and Posner tasks being most sensitive to group effects. Due to the paucity of studies and variability in design and measurement, no conclusions could be reached regarding manipulation or induction of attentional bias in good sleepers. Results from the relatively small number of studies support the presence of sleep-related attentional bias in insomnia; however, its role in the development and/or maintenance of insomnia remains to be elucidated. We set out a research agenda aimed at advancing the understanding of sleep-related attention bias.
Improved Arctic sea ice thickness projections using bias-corrected CMIP5 simulations
Melia, N.; Haines, K.; Hawkins, E.
2015-12-01
Projections of Arctic sea ice thickness (SIT) have the potential to inform stakeholders about accessibility to the region, but are currently rather uncertain. The latest suite of CMIP5 global climate models (GCMs) produce a wide range of simulated SIT in the historical period (1979-2014) and exhibit various biases when compared with the Pan-Arctic Ice-Ocean Modelling and Assimilation System (PIOMAS) sea ice reanalysis. We present a new method to constrain such GCM simulations of SIT via a statistical bias correction technique. The bias correction successfully constrains the spatial SIT distribution and temporal variability in the CMIP5 projections whilst retaining the climatic fluctuations from individual ensemble members. The bias correction acts to reduce the spread in projections of SIT and reveals the significant contributions of climate internal variability in the first half of the century and of scenario uncertainty from the mid-century onwards. The projected date of ice-free conditions in the Arctic under the RCP8.5 high emission scenario occurs in the 2050s, which is a decade earlier than without the bias correction, with potentially significant implications for stakeholders in the Arctic such as the shipping industry. The bias correction methodology developed could be similarly applied to other variables to reduce spread in climate projections more generally.
Improved Arctic Sea Ice Thickness Projections Using Bias Corrected CMIP5 Simulations
Melia, N.; Hawkins, E.; Haines, K.
2015-12-01
Projections of Arctic sea ice thickness (SIT) have the potential to inform stakeholders about accessibility to the region, but are currently rather uncertain. The latest suite of CMIP5 Global Climate Models (GCMs) produce a wide range of simulated SIT in the historical period (1979-2014) and exhibit various spatial and temporal biases when compared with the Pan-Arctic Ice Ocean Modelling and Assimilation System (PIOMAS) sea ice reanalysis. We present a new method to constrain such GCM simulations of SIT to narrow projection uncertainty via a statistical bias correction technique. The bias correction successfully constrains the spatial SIT distribution and temporal variability in the CMIP5 projections whilst retaining the climatic fluctuations from individual ensemble members. The bias correction acts to reduce the uncertainty in projections of SIT and reveals the significant contributions of sea ice internal variability in the first half of the century and of scenario uncertainty from mid-century onwards. The projected date of ice-free conditions in the Arctic under the RCP8.5 high emission scenario occurs in the 2050s, which is a decade earlier than without the bias correction, with potentially significant implications for stakeholders in the Arctic such as the shipping industry. The bias correction methodology developed could be similarly applied to other variables to narrow uncertainty in climate projections more generally.
Introducing decorated HODs: modelling assembly bias in the galaxy-halo connection
Hearin, Andrew P.; Zentner, Andrew R.; van den Bosch, Frank C.; Campbell, Duncan; Tollerud, Erik
2016-08-01
The connection between galaxies and dark matter haloes is often inferred from data using probabilistic models, such as the halo occupation distribution (HOD). Conventional HOD formulations assume that only halo mass governs the galaxy-halo connection. Violations of this assumption, known as galaxy assembly bias, threaten the HOD programme. We introduce decorated HODs, a new, flexible class of models designed to account for assembly bias. Decorated HODs minimally expand the parameter space and maximize the independence between traditional and novel HOD parameters. We use decorated HODs to quantify the influence of assembly bias on clustering and lensing statistics. For SDSS-like samples, the impact of assembly bias on galaxy clustering can be as large as a factor of 2 on r ˜ 200 kpc scales and ˜15 per cent in the linear regime. Assembly bias can either enhance or diminish clustering on large scales, but generally increases clustering on scales r ≲ 1 Mpc. We performed our calculations with HALOTOOLS, an open-source, community-driven PYTHON package for studying the galaxy-halo connection (http://halotools.readthedocs.org). We conclude by describing the use of decorated HODs to treat assembly bias in otherwise conventional likelihood analyses.
Finding seeds for segmentation using statistical fusion
Xing, Fangxu; Asman, Andrew J.; Prince, Jerry L.; Landman, Bennett A.
2012-02-01
Image labeling is an essential step for quantitative analysis of medical images. Many image labeling algorithms require seed identification in order to initialize segmentation algorithms such as region growing, graph cuts, and the random walker. Seeds are usually placed manually by human raters, which makes these algorithms semi-automatic and can be prohibitive for very large datasets. In this paper an automatic algorithm for placing seeds using multi-atlas registration and statistical fusion is proposed. Atlases containing the centers of mass of a collection of neuroanatomical objects are deformably registered in a training set to determine where these centers of mass go after labels transformed by registration. The biases of these transformations are determined and incorporated in a continuous form of Simultaneous Truth And Performance Level Estimation (STAPLE) fusion, thereby improving the estimates (on average) over a single registration strategy that does not incorporate bias or fusion. We evaluate this technique using real 3D brain MR image atlases and demonstrate its efficacy on correcting the data bias and reducing the fusion error.
Statistics 101 for Radiologists.
Anvari, Arash; Halpern, Elkan F; Samir, Anthony E
2015-10-01
Diagnostic tests have wide clinical applications, including screening, diagnosis, measuring treatment effect, and determining prognosis. Interpreting diagnostic test results requires an understanding of key statistical concepts used to evaluate test efficacy. This review explains descriptive statistics and discusses probability, including mutually exclusive and independent events and conditional probability. In the inferential statistics section, a statistical perspective on study design is provided, together with an explanation of how to select appropriate statistical tests. Key concepts in recruiting study samples are discussed, including representativeness and random sampling. Variable types are defined, including predictor, outcome, and covariate variables, and the relationship of these variables to one another. In the hypothesis testing section, we explain how to determine if observed differences between groups are likely to be due to chance. We explain type I and II errors, statistical significance, and study power, followed by an explanation of effect sizes and how confidence intervals can be used to generalize observed effect sizes to the larger population. Statistical tests are explained in four categories: t tests and analysis of variance, proportion analysis tests, nonparametric tests, and regression techniques. We discuss sensitivity, specificity, accuracy, receiver operating characteristic analysis, and likelihood ratios. Measures of reliability and agreement, including κ statistics, intraclass correlation coefficients, and Bland-Altman graphs and analysis, are introduced. PMID:26466186
Huizingh, Eelko K. R. E.
2007-01-01
Accessibly written and easy to use, "Applied Statistics Using SPSS" is an all-in-one self-study guide to SPSS and do-it-yourself guide to statistics. What is unique about Eelko Huizingh's approach is that this book is based around the needs of undergraduate students embarking on their own research project, and its self-help style is designed to…
Reform in Statistical Education
Huck, Schuyler W.
2007-01-01
Two questions are considered in this article: (a) What should professionals in school psychology do in an effort to stay current with developments in applied statistics? (b) What should they do with their existing knowledge to move from surface understanding of statistics to deep understanding? Written for school psychologists who have completed…
Bangladesh; Statistical Appendix
International Monetary Fund
1995-01-01
The paper presents statistical data on gross domestic product, agricultural production, manufacturing production, energy statistics, retail prices of petroleum products, consumer price index, central government operations, revenues, and central expenditure in Bangladesh. It also presents the central government food account, consolidated accounts and profits of nonfinancial public enterprises, government domestic securities, monetary survey, balance sheet of the monetary authorities, interest ...
DEFF Research Database (Denmark)
Lauritzen, Steffen Lilholt
This book studies the brilliant Danish 19th Century astronomer, T.N. Thiele who made important contributions to statistics, actuarial science, astronomy and mathematics. The most important of these contributions in statistics are translated into English for the first time, and the text includes...
Introduction to BIS statistics
Bank for International Settlements
2015-01-01
The BIS has expanded its statistics by publishing additional data, revamping their dissemination and strengthening their policy orientation. This special feature, prepared by members of the BIS Monetary and Economic Department, briefly describes each BIS data set and explains how the statistics can be used for analysis.
Practical statistics simply explained
Langley, Dr Russell A
1971-01-01
For those who need to know statistics but shy away from math, this book teaches how to extract truth and draw valid conclusions from numerical data using logic and the philosophy of statistics rather than complex formulae. Lucid discussion of averages and scatter, investigation design, more. Problems with solutions.
Handbook of Spatial Statistics
Gelfand, Alan E
2010-01-01
Offers an introduction detailing the evolution of the field of spatial statistics. This title focuses on the three main branches of spatial statistics: continuous spatial variation (point referenced data); discrete spatial variation, including lattice and areal unit data; and, spatial point patterns.
The purpose of the Disability Statistics Center is to produce and disseminate statistical information on disability and the status of people with disabilities in American society and to establish and monitor indicators of how conditions are changing over time to meet their health...
Statistics 101 for Radiologists.
Anvari, Arash; Halpern, Elkan F; Samir, Anthony E
2015-10-01
Diagnostic tests have wide clinical applications, including screening, diagnosis, measuring treatment effect, and determining prognosis. Interpreting diagnostic test results requires an understanding of key statistical concepts used to evaluate test efficacy. This review explains descriptive statistics and discusses probability, including mutually exclusive and independent events and conditional probability. In the inferential statistics section, a statistical perspective on study design is provided, together with an explanation of how to select appropriate statistical tests. Key concepts in recruiting study samples are discussed, including representativeness and random sampling. Variable types are defined, including predictor, outcome, and covariate variables, and the relationship of these variables to one another. In the hypothesis testing section, we explain how to determine if observed differences between groups are likely to be due to chance. We explain type I and II errors, statistical significance, and study power, followed by an explanation of effect sizes and how confidence intervals can be used to generalize observed effect sizes to the larger population. Statistical tests are explained in four categories: t tests and analysis of variance, proportion analysis tests, nonparametric tests, and regression techniques. We discuss sensitivity, specificity, accuracy, receiver operating characteristic analysis, and likelihood ratios. Measures of reliability and agreement, including κ statistics, intraclass correlation coefficients, and Bland-Altman graphs and analysis, are introduced.
Council of Ontario Universities, Toronto.
Summary statistics on application and registration patterns of applicants wishing to pursue full-time study in first-year places in Ontario universities (for the fall of 1987) are given. Data on registrations were received indirectly from the universities as part of their annual submission of USIS/UAR enrollment data to Statistics Canada and MCU.…
Practical statistics for educators
Ravid, Ruth
2014-01-01
Practical Statistics for Educators, Fifth Edition, is a clear and easy-to-follow text written specifically for education students in introductory statistics courses and in action research courses. It is also a valuable resource and guidebook for educational practitioners who wish to study their own settings.
Per Object statistical analysis
DEFF Research Database (Denmark)
Groom, Geoffrey Brian
2008-01-01
This RS code is to do Object-by-Object analysis of each Object's sub-objects, e.g. statistical analysis of an object's individual image data pixels. Statistics, such as percentiles (so-called "quartiles") are derived by the process, but the return of that can only be a Scene Variable, not an Obje...
Statistical error analysis of reactivity measurement
Energy Technology Data Exchange (ETDEWEB)
Thammaluckan, Sithisak; Hah, Chang Joo [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)
2013-10-15
After statistical analysis, it was confirmed that each group were sampled from same population. It is observed in Table 7 that the mean error decreases as core size increases. Application of bias factor obtained from this research reduces mean error further. The point kinetic model had been used to measure control rod worth without 3D spatial information of neutron flux or power distribution, which causes inaccurate result. Dynamic Control rod Reactivity Measurement (DCRM) was employed to take into account of 3D spatial information of flux in the point kinetics model. The measured bank worth probably contains some uncertainty such as methodology uncertainty and measurement uncertainty. Those uncertainties may varies with size of core and magnitude of reactivity. The goal of this research is to investigate the effect of core size and magnitude of control rod worth on the error of reactivity measurement using statistics.
Python for probability, statistics, and machine learning
Unpingco, José
2016-01-01
This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Modern Python modules like Pandas, Sympy, and Scikit-learn are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowl...
Contextual modulation of biases in face recognition.
Directory of Open Access Journals (Sweden)
Fatima Maria Felisberti
Full Text Available BACKGROUND: The ability to recognize the faces of potential cooperators and cheaters is fundamental to social exchanges, given that cooperation for mutual benefit is expected. Studies addressing biases in face recognition have so far proved inconclusive, with reports of biases towards faces of cheaters, biases towards faces of cooperators, or no biases at all. This study attempts to uncover possible causes underlying such discrepancies. METHODOLOGY AND FINDINGS: Four experiments were designed to investigate biases in face recognition during social exchanges when behavioral descriptors (prosocial, antisocial or neutral embedded in different scenarios were tagged to faces during memorization. Face recognition, measured as accuracy and response latency, was tested with modified yes-no, forced-choice and recall tasks (N = 174. An enhanced recognition of faces tagged with prosocial descriptors was observed when the encoding scenario involved financial transactions and the rules of the social contract were not explicit (experiments 1 and 2. Such bias was eliminated or attenuated by making participants explicitly aware of "cooperative", "cheating" and "neutral/indifferent" behaviors via a pre-test questionnaire and then adding such tags to behavioral descriptors (experiment 3. Further, in a social judgment scenario with descriptors of salient moral behaviors, recognition of antisocial and prosocial faces was similar, but significantly better than neutral faces (experiment 4. CONCLUSION: The results highlight the relevance of descriptors and scenarios of social exchange in face recognition, when the frequency of prosocial and antisocial individuals in a group is similar. Recognition biases towards prosocial faces emerged when descriptors did not state the rules of a social contract or the moral status of a behavior, and they point to the existence of broad and flexible cognitive abilities finely tuned to minor changes in social context.
Affective Biases in Humans and Animals.
Robinson, E S J; Roiser, J P
2016-01-01
Depression is one of the most common but poorly understood psychiatric conditions. Although drug treatments and psychological therapies are effective in some patients, many do not achieve full remission and some patients receive no apparent benefit. Developing new improved treatments requires a better understanding of the aetiology of symptoms and evaluation of novel therapeutic targets in pre-clinical studies. Recent developments in our understanding of the basic cognitive processes that may contribute to the development of depression and its treatment offer new opportunities for both clinical and pre-clinical research. This chapter discusses the clinical evidence supporting a cognitive neuropsychological model of depression and antidepressant efficacy, and how this information may be usefully translated to pre-clinical investigation. Studies using neuropsychological tests in depressed patients and at risk populations have revealed basic negative emotional biases and disrupted reward and punishment processing, which may also impact on non-affective cognition. These affective biases are sensitive to antidepressant treatments with early onset effects observed, suggesting an important role in recovery. This clinical work into affective biases has also facilitated back-translation to animals and the development of assays to study affective biases in rodents. These animal studies suggest that, similar to humans, rodents in putative negative affective states exhibit negative affective biases on decision-making and memory tasks. Antidepressant treatments also induce positive biases in these rodent tasks, supporting the translational validity of this approach. Although still in the early stages of development and validation, affective biases in depression have the potential to offer new insights into the clinical condition, as well as facilitating the development of more translational approaches for pre-clinical studies. PMID:27660073
Statistical Methods for Astronomy
Feigelson, Eric D
2012-01-01
This review outlines concepts of mathematical statistics, elements of probability theory, hypothesis tests and point estimation for use in the analysis of modern astronomical data. Least squares, maximum likelihood, and Bayesian approaches to statistical inference are treated. Resampling methods, particularly the bootstrap, provide valuable procedures when distributions functions of statistics are not known. Several approaches to model selection and good- ness of fit are considered. Applied statistics relevant to astronomical research are briefly discussed: nonparametric methods for use when little is known about the behavior of the astronomical populations or processes; data smoothing with kernel density estimation and nonparametric regression; unsupervised clustering and supervised classification procedures for multivariate problems; survival analysis for astronomical datasets with nondetections; time- and frequency-domain times series analysis for light curves; and spatial statistics to interpret the spati...
Statistical laws in linguistics
Altmann, Eduardo G
2015-01-01
Zipf's law is just one out of many universal laws proposed to describe statistical regularities in language. Here we review and critically discuss how these laws can be statistically interpreted, fitted, and tested (falsified). The modern availability of large databases of written text allows for tests with an unprecedent statistical accuracy and also a characterization of the fluctuations around the typical behavior. We find that fluctuations are usually much larger than expected based on simplifying statistical assumptions (e.g., independence and lack of correlations between observations).These simplifications appear also in usual statistical tests so that the large fluctuations can be erroneously interpreted as a falsification of the law. Instead, here we argue that linguistic laws are only meaningful (falsifiable) if accompanied by a model for which the fluctuations can be computed (e.g., a generative model of the text). The large fluctuations we report show that the constraints imposed by linguistic laws...
Introduction to Bayesian statistics
Bolstad, William M
2016-01-01
There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this Third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian staistics. The author continues to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inferenfe cfor discrete random variables, bionomial proprotion, Poisson, normal mean, and simple linear regression. In addition, newly-developing topics in the field are presented in four new chapters: Bayesian inference with unknown mean and variance; Bayesian inference for Multivariate Normal mean vector; Bayesian inference for Multiple Linear RegressionModel; and Computati...
Geometrisation of Statistical Mechanics
Brody, D C; Brody, Dorje C.; Hughston, Lane P.
1997-01-01
Classical and quantum statistical mechanics are cast here in the language of projective geometry to provide a unified geometrical framework for statistical physics. After reviewing the Hilbert space formulation of classical statistical thermodynamics, we introduce projective geometry as a basis for analysing probabilistic aspects of statistical physics. In particular, the specification of a canonical polarity on $RP^{n}$ induces a Riemannian metric on the state space of statistical mechanics. In the case of the canonical ensemble, we show that equilibrium thermal states are determined by the Hamiltonian gradient flow with respect to this metric. This flow is concisely characterised by the fact that it induces a projective automorphism on the state manifold. The measurement problem for thermal systems is studied by the introduction of the concept of a random state. The general methodology is then extended to include the quantum mechanical dynamics of equilibrium thermal states. In this case the relevant state ...
Hou, Yukun; Chen, Hua; Xu, Chongyu; Hu, Kang
2016-04-01
Statistical downscaling methods are a common tool to compensate for the gaps between large-scale climate model simulations and station-scale observations. This study evaluates the performance of the raw precipitation from National Centers for Environmental Prediction (NCEP), outputs of Global Climate Model (GCM)-NorESM and corresponding Regional Climate Model (RCM)-the East Asian regional climate model driven by WRF model driven with NorESM. Meanwhile, their bias-corrected series by four different bias correction methods are simultaneously evaluated in order to find whether NCEP with observation coupled or RCM with modified spatial distribution of surface climate can have a better performance than GCM on analyzing hydrological impact. The Xin'anjiang lumped hydrological model is used to assess the hydrological impacts by simulating the streamflows in Xiangjiang basin with the corresponding observed, model-simulated and bias-corrected precipitation as input. The results show that hydrological simulations using the RCM and NCEP historical precipitation do not have a better agreement with observed runoff than using raw GCM data as input in this case study. However, when the raw precipitation of climate models is bias-corrected, an obvious improvement is obtained from all the climate models, and the bias-corrected RCM precipitation gives the best fitness in the runoff simulations. Comparing different bias correction methods with the same climate model, the method with occurrence and intensity adjustment outperforms other methods in the runoff simulation. It can be inferred that without bias correction, it can be hardly concluded that NCEP or RCM brings an improvement of precipitation simulation from GCM for driving hydrological models. However, the RCM precipitation corrected by a proper bias correction method provides better runoff simulation results over other climate datasets.
Cancer Data and Statistics Tools
... in Cancer Moonshot Stay Informed Cancer Data and Statistics Tools Recommend on Facebook Tweet Share Compartir United States Cancer Statistics The United States Cancer Statistics (USCS): Incidence and ...
Colin, Pierre; Kravtsov, A V; Colin, Pedro; Klypin, Anatoly; Kravtsov, Andrey V.
2000-01-01
We use N-body simulations to study the velocity bias of dark matter halos, the difference in the velocity fields of dark matter and halos, in a flat low- density LCDM model. The high force, 2kpc/h, and mass, 10^9Msun/h, resolution allows dark matter halos to survive in very dense environments of groups and clusters making it possible to use halos as galaxy tracers. We find that the velocity bias pvb measured as a ratio of pairwise velocities of the halos to that of the dark matter evolves with time and depends on scale. At high redshifts (z ~5) halos move generally faster than the dark matter almost on all scales: pvb(r)~1.2, r>0.5Mpc/h. At later moments the bias decreases and gets below unity on scales less than r=5Mpc/h: pvb(r)~(0.6-0.8) at z=0. We find that the evolution of the pairwise velocity bias follows and probably is defined by the spatial antibias of the dark matter halos at small scales. One-point velocity bias b_v, defined as the ratio of the rms velocities of halos and dark matter, provides a mo...
Electrostatically biased binding of kinesin to microtubules.
Directory of Open Access Journals (Sweden)
Barry J Grant
2011-11-01
Full Text Available The minimum motor domain of kinesin-1 is a single head. Recent evidence suggests that such minimal motor domains generate force by a biased binding mechanism, in which they preferentially select binding sites on the microtubule that lie ahead in the progress direction of the motor. A specific molecular mechanism for biased binding has, however, so far been lacking. Here we use atomistic Brownian dynamics simulations combined with experimental mutagenesis to show that incoming kinesin heads undergo electrostatically guided diffusion-to-capture by microtubules, and that this produces directionally biased binding. Kinesin-1 heads are initially rotated by the electrostatic field so that their tubulin-binding sites face inwards, and then steered towards a plus-endwards binding site. In tethered kinesin dimers, this bias is amplified. A 3-residue sequence (RAK in kinesin helix alpha-6 is predicted to be important for electrostatic guidance. Real-world mutagenesis of this sequence powerfully influences kinesin-driven microtubule sliding, with one mutant producing a 5-fold acceleration over wild type. We conclude that electrostatic interactions play an important role in the kinesin stepping mechanism, by biasing the diffusional association of kinesin with microtubules.
CD bias control on hole pattern
Koike, Kyohei; Hara, Arisa; Natori, Sakurako; Yamauchi, Shohei; Yamato, Masatoshi; Oyama, Kenichi; Yaegashi, Hidetami
2016-03-01
Gridded design rules[1] is major process in configuring logic circuit used 193-immersion lithography. In the scaling of grid patterning, we can make 10nm order line and space pattern by using multiple patterning techniques such as self-aligned multiple patterning (SAMP) and litho-etch- litho-etch (LELE)[2][3][5] . On the other hand, Line cut process has some error parameters such as pattern defect, placement error, roughness and X-Y CD bias with the decreasing scale. Especially roughness and X-Y CD bias are paid attention because it cause cut error and pattern defect. In this case, we applied some smoothing process to care hole roughness[4]. Each smoothing process showed different effect on X-Y CD bias. In this paper, we will report the pattern controllability comparison of trench and block + inverse. It include X-Y CD bias, roughness and process usability. Furthermore we will discuss optimum method focused on X-Y CD bias when we use additional process such as smoothing and shrink etching .
Social biases determine spatiotemporal sparseness of ciliate mating heuristics.
Clark, Kevin B
2012-01-01
Ciliates become highly social, even displaying animal-like qualities, in the joint presence of aroused conspecifics and nonself mating pheromones. Pheromone detection putatively helps trigger instinctual and learned courtship and dominance displays from which social judgments are made about the availability, compatibility, and fitness representativeness or likelihood of prospective mates and rivals. In earlier studies, I demonstrated the heterotrich Spirostomum ambiguum improves mating competence by effecting preconjugal strategies and inferences in mock social trials via behavioral heuristics built from Hebbian-like associative learning. Heuristics embody serial patterns of socially relevant action that evolve into ordered, topologically invariant computational networks supporting intra- and intermate selection. S. ambiguum employs heuristics to acquire, store, plan, compare, modify, select, and execute sets of mating propaganda. One major adaptive constraint over formation and use of heuristics involves a ciliate's initial subjective bias, responsiveness, or preparedness, as defined by Stevens' Law of subjective stimulus intensity, for perceiving the meaningfulness of mechanical pressures accompanying cell-cell contacts and additional perimating events. This bias controls durations and valences of nonassociative learning, search rates for appropriate mating strategies, potential net reproductive payoffs, levels of social honesty and deception, successful error diagnosis and correction of mating signals, use of insight or analysis to solve mating dilemmas, bioenergetics expenditures, and governance of mating decisions by classical or quantum statistical mechanics. I now report this same social bias also differentially affects the spatiotemporal sparseness, as measured with metric entropy, of ciliate heuristics. Sparseness plays an important role in neural systems through optimizing the specificity, efficiency, and capacity of memory representations. The present
Statistical downscaling using K-nearest neighbors
Gangopadhyay, Subhrendu; Clark, Martyn; Rajagopalan, Balaji
2005-02-01
Statistical downscaling provides a technique for deriving local-scale information of precipitation and temperature from numerical weather prediction model output. The K-nearest neighbor (K-nn) is a new analog-type approach that is used in this paper to downscale the National Centers for Environmental Prediction 1998 medium-range forecast model output. The K-nn algorithm queries days similar to a given feature vector in this archive and using empirical orthogonal function analysis identifies a subset of days (K) similar to the feature day. These K days are then weighted using a bisquare weight function and randomly sampled to generate ensembles. A set of 15 medium-range forecast runs was used, and seven ensemble members were generated from each run. The ensemble of 105 members was then used to select the local-scale precipitation and temperature values in four diverse basins across the contiguous United States. These downscaled precipitation and temperature estimates were subsequently analyzed to test the performance of this downscaling approach. The downscaled ensembles were evaluated in terms of bias, the ranked probability skill score as a measure of forecast skill, spatial covariability between stations, temporal persistence, consistency between variables, and conditional bias and to develop spread-skill relationships. Though this approach does not explicitly model the space-time variability of the weather fields at each individual station, the above statistics were extremely well captured. The K-nn method was also compared with a multiple-linear-regression-based downscaling model.
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
Significance analysis of lexical bias in microarray data
Directory of Open Access Journals (Sweden)
Falkow Stanley
2003-04-01
Full Text Available Abstract Background Genes that are determined to be significantly differentially regulated in microarray analyses often appear to have functional commonalities, such as being components of the same biochemical pathway. This results in certain words being under- or overrepresented in the list of genes. Distinguishing between biologically meaningful trends and artifacts of annotation and analysis procedures is of the utmost importance, as only true biological trends are of interest for further experimentation. A number of sophisticated methods for identification of significant lexical trends are currently available, but these methods are generally too cumbersome for practical use by most microarray users. Results We have developed a tool, LACK, for calculating the statistical significance of apparent lexical bias in microarray datasets. The frequency of a user-specified list of search terms in a list of genes which are differentially regulated is assessed for statistical significance by comparison to randomly generated datasets. The simplicity of the input files and user interface targets the average microarray user who wishes to have a statistical measure of apparent lexical trends in analyzed datasets without the need for bioinformatics skills. The software is available as Perl source or a Windows executable. Conclusion We have used LACK in our laboratory to generate biological hypotheses based on our microarray data. We demonstrate the program's utility using an example in which we confirm significant upregulation of SPI-2 pathogenicity island of Salmonella enterica serovar Typhimurium by the cation chelator dipyridyl.
Thermospheric density model biases at the 23rd sunspot maximum
Pardini, C.; Moe, K.; Anselmo, L.
2012-07-01
statistically significant. The minimum average biases were obtained with JB2008, NRLMSISE-00 and GOST-2004. Above 500 km, where only one satellite was analyzed (at 630 km), and errors tend to increase with altitude, it cannot be asserted that the calculated biases are significant. Nevertheless, they are presented to show how the various models diverge at higher altitudes. Around 630 km, NRLMSISE-00 had a negligible average bias, while the other models underestimated (GOST-2004) or overestimated the average density, by amounts varying between 6% and 16%. However, in terms of semi-major axis root mean square residuals, JB2006 and JB2008 were the best in any case. Below 500 km, the short-term behavior of the models was also investigated by fitting the semi-major axis decay over 30-day arcs. The resulting fitted drag coefficients displayed a significant variability, probably associated with mismodeled density variations, but JB2008, followed by JB2006, provided the smallest semi-major axis residuals and a reduced short-term variability of the density bias at just a few frequencies, having been probably successful in removing a significant fraction of the mismodeling sources.
Expectancy biases in fear and anxiety and their link to biases in attention.
Aue, Tatjana; Okon-Singer, Hadas
2015-12-01
Healthy individuals often exhibit prioritized processing of aversive information, as manifested in enhanced orientation of attention to threatening stimuli compared with neutral items. In contrast to this adaptive behavior, anxious, fearful, and phobic individuals show exaggerated attention biases to threat. In addition, they overestimate the likelihood of encountering their feared stimulus and the severity of the consequences; both are examples of expectancy biases. The co-occurrence of attention and expectancy biases in fear and anxiety raises the question about causal influences. Herein, we summarize findings related to expectancy biases in fear and anxiety, and their association with attention biases. We suggest that evidence calls for more comprehensive research strategies in the investigation of mutual influences between expectancy and attention biases, as well as their combined effects on fear and anxiety. Moreover, both types of bias need to be related to other types of distorted information processing commonly observed in fear and anxiety (e.g., memory and interpretation biases). Finally, we propose new research directions that may be worth considering in developing more effective treatments for anxiety disorders.
Energy Technology Data Exchange (ETDEWEB)
Makhnovskii, Yurii A. [Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Leninsky Prospect 29, Moscow 119991 (Russian Federation); Berezhkovskii, Alexander M. [Mathematical and Statistical Computing Laboratory, Division of Computational Bioscience, Center for Information Technology, National Institutes of Health, Bethesda, Maryland 20819 (United States); Antipov, Anatoly E. [Faculty of Fundamental Physics and Chemical Engineering, Moscow State University, GSP-1, 1-51 Leninskie Gory, Moscow 119991 (Russian Federation); Zitserman, Vladimir Yu. [Joint Institute for High Temperatures, Russian Academy of Sciences, Izhorskaya 13, Bldg. 2, Moscow 125412 (Russian Federation)
2015-11-07
This paper is devoted to particle transport in a tube formed by alternating wide and narrow sections, in the presence of an external biasing force. The focus is on the effective transport coefficients—mobility and diffusivity, as functions of the biasing force and the geometric parameters of the tube. Dependences of the effective mobility and diffusivity on the tube geometric parameters are known in the limiting cases of no bias and strong bias. The approximations used to obtain these results are inapplicable at intermediate values of the biasing force. To bridge the two limits Brownian dynamics simulations were run to determine the transport coefficients at intermediate values of the force. The simulations were performed for a representative set of tube geometries over a wide range of the biasing force. They revealed that there is a range of the narrow section length, where the force dependence of the mobility has a maximum. In contrast, the diffusivity is a monotonically increasing function of the force. A simple formula is proposed, which reduces to the known dependences of the diffusivity on the tube geometric parameters in both limits of zero and strong bias. At intermediate values of the biasing force, the formula catches the diffusivity dependence on the narrow section length, if the radius of these sections is not too small.
Strick, M.A.; Stoeckart, P.F.; Dijksterhuis, A.J.
2015-01-01
It is a common research finding that conscious thought helps people to avoid racial discrimination. These three experiments, however, illustrate that conscious thought may increase biased face memory, which leads to increased judgment bias (i.e., preferring White to Black individuals). In Experiment
Placebo effect studies are susceptible to response bias and to other types of biases
DEFF Research Database (Denmark)
Hróbjartsson, Asbjørn; Kaptchuk, Ted J; Miller, Franklin G
2011-01-01
Investigations of the effect of placebo are often challenging to conduct and interpret. The history of placebo shows that assessment of its clinical significance has a real potential to be biased. We analyze and discuss typical types of bias in studies on placebo....
Wallis, W Allen
2014-01-01
Focusing on everyday applications as well as those of scientific research, this classic of modern statistical methods requires little to no mathematical background. Readers develop basic skills for evaluating and using statistical data. Lively, relevant examples include applications to business, government, social and physical sciences, genetics, medicine, and public health. ""W. Allen Wallis and Harry V. Roberts have made statistics fascinating."" - The New York Times ""The authors have set out with considerable success, to write a text which would be of interest and value to the student who,
Statistical Pattern Recognition
Webb, Andrew R
2011-01-01
Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields,
Statistics a complete introduction
Graham, Alan
2013-01-01
Statistics: A Complete Introduction is the most comprehensive yet easy-to-use introduction to using Statistics. Written by a leading expert, this book will help you if you are studying for an important exam or essay, or if you simply want to improve your knowledge. The book covers all the key areas of Statistics including graphs, data interpretation, spreadsheets, regression, correlation and probability. Everything you will need is here in this one book. Each chapter includes not only an explanation of the knowledge and skills you need, but also worked examples and test questions.
Mauro, John
2013-01-01
Written to reveal statistical deceptions often thrust upon unsuspecting journalists, this book views the use of numbers from a public perspective. Illustrating how the statistical naivete of journalists often nourishes quantitative misinformation, the author's intent is to make journalists more critical appraisers of numerical data so that in reporting them they do not deceive the public. The book frequently uses actual reported examples of misused statistical data reported by mass media and describes how journalists can avoid being taken in by them. Because reports of survey findings seldom g
Huizingh, Eelko K R E
2007-01-01
Accessibly written and easy to use, Applied Statistics Using SPSS is an all-in-one self-study guide to SPSS and do-it-yourself guide to statistics. Based around the needs of undergraduate students embarking on their own research project, the text's self-help style is designed to boost the skills and confidence of those that will need to use SPSS in the course of doing their research project. The book is pedagogically well developed and contains many screen dumps and exercises, glossary terms and worked examples. Divided into two parts, Applied Statistics Using SPSS covers :
Evolutionary Statistical Procedures
Baragona, Roberto; Poli, Irene
2011-01-01
This proposed text appears to be a good introduction to evolutionary computation for use in applied statistics research. The authors draw from a vast base of knowledge about the current literature in both the design of evolutionary algorithms and statistical techniques. Modern statistical research is on the threshold of solving increasingly complex problems in high dimensions, and the generalization of its methodology to parameters whose estimators do not follow mathematically simple distributions is underway. Many of these challenges involve optimizing functions for which analytic solutions a
D'Alessio, Michael
2012-01-01
AP Statistics Crash Course - Gets You a Higher Advanced Placement Score in Less Time Crash Course is perfect for the time-crunched student, the last-minute studier, or anyone who wants a refresher on the subject. AP Statistics Crash Course gives you: Targeted, Focused Review - Study Only What You Need to Know Crash Course is based on an in-depth analysis of the AP Statistics course description outline and actual Advanced Placement test questions. It covers only the information tested on the exam, so you can make the most of your valuable study time. Our easy-to-read format covers: exploring da
Statistics of football dynamics
Mendes, R S; Anteneodo, C
2007-01-01
We investigate the dynamics of football matches. Our goal is to characterize statistically the temporal sequence of ball movements in this collective sport game, searching for traits of complex behavior. Data were collected over a variety of matches in South American, European and World championships throughout 2005 and 2006. We show that the statistics of ball touches presents power-law tails and can be described by $q$-gamma distributions. To explain such behavior we propose a model that provides information on the characteristics of football dynamics. Furthermore, we discuss the statistics of duration of out-of-play intervals, not directly related to the previous scenario.
Statistics of genome architecture
International Nuclear Information System (INIS)
The main statistical distributions applicable to the analysis of genome architecture and genome tracks are briefly discussed and critically assessed. Although the observed features in distributions of element lengths can be equally well fitted by the different statistical approximations, the interpretation of observed regularities may strongly depend on the chosen scheme. We discuss the possible evolution scenarios and describe the main characteristics obtained with different distributions. The expression for the assessment of levels in hierarchical chromatin folding is derived and the quantitative measure of genome architecture inhomogeneity is suggested. This theory provides the ground for the regular statistical study of genome architecture and genome tracks.
Liao, Tim Futing
2011-01-01
An incomparably useful examination of statistical methods for comparisonThe nature of doing science, be it natural or social, inevitably calls for comparison. Statistical methods are at the heart of such comparison, for they not only help us gain understanding of the world around us but often define how our research is to be carried out. The need to compare between groups is best exemplified by experiments, which have clearly defined statistical methods. However, true experiments are not always possible. What complicates the matter more is a great deal of diversity in factors that are not inde
Validation of models with constant bias: an applied approach
Directory of Open Access Journals (Sweden)
Salvador Medina-Peralta
2014-06-01
Full Text Available Objective. This paper presents extensions to the statistical validation method based on the procedure of Freese when a model shows constant bias (CB in its predictions and illustrate the method with data from a new mechanistic model that predict weight gain in cattle. Materials and methods. The extensions were the hypothesis tests and maximum anticipated error for the alternative approach, and the confidence interval for a quantile of the distribution of errors. Results. The model evaluated showed CB, once the CB is removed and with a confidence level of 95%, the magnitude of the error does not exceed 0.575 kg. Therefore, the validated model can be used to predict the daily weight gain of cattle, although it will require an adjustment in its structure based on the presence of CB to increase the accuracy of its forecasts. Conclusions. The confidence interval for the 1-α quantile of the distribution of errors after correcting the constant bias, allows determining the top limit for the magnitude of the error of prediction and use it to evaluate the evolution of the model in the forecasting of the system. The confidence interval approach to validate a model is more informative than the hypothesis tests for the same purpose.
Subhalo abundance matching and assembly bias in the EAGLE simulation
Chaves-Montero, Jonás; Angulo, Raul E.; Schaye, Joop; Schaller, Matthieu; Crain, Robert A.; Furlong, Michelle; Theuns, Tom
2016-08-01
Subhalo abundance matching (SHAM) is a widely used method to connect galaxies with dark matter structures in numerical simulations. SHAM predictions agree remarkably well with observations, yet they still lack strong theoretical support. We examine the performance, implementation, and assumptions of SHAM using the `Evolution and Assembly of Galaxies and their Environment' (EAGLE) project simulations. We find that Vrelax, the highest value of the circular velocity attained by a subhalo while it satisfies a relaxation criterion, is the subhalo property that correlates most strongly with galaxy stellar mass (Mstar). Using this parameter in SHAM, we retrieve the real-space clustering of EAGLE to within our statistical uncertainties on scales greater than 2 Mpc for galaxies with 8.77 assembly bias. We demonstrate assembly bias alters the clustering in EAGLE by 20 per cent and Vrelax captures its effect to within 15 per cent. We trace small differences in the clustering to the failure of SHAM as typically implemented, i.e. the Mstar assigned to a subhalo does not depend on (i) its host halo mass, (ii) whether it is a central or a satellite. In EAGLE, we find that these assumptions are not completely satisfied.
Godleski, Stephanie A.; Ostrov, Jamie M.
2010-01-01
The present study used both categorical and dimensional approaches to test the association between relational and physical aggression and hostile intent attributions for both relational and instrumental provocation situations using the National Institute of Child Health and Human Development longitudinal Study of Early Child Care and Youth…
Linearity Limits of Biased 1337 Trap Detectors
Balling, Petr
2015-01-01
The upper power limit of linear response of light trap detectors was recently measured [2,3]. We have completed this measurement with test of traps with bias voltage at several visible wavelengths using silicon photodiodes Hamamatsu S1337 1010 and made a brief test of S5227 1010. Bias extends the linearity limit by factor of more than 10 for very narrow beams and more than 30 for wide beams [5]. No irreversible changes were detected even for the highest irradiance of 33 W/cm2 at 406nm. Here we present measurement of minimal bias voltage necessary for 99%, 99.8% and 99.95% linearity for several beam sizes.
Reciprocity-induced bias in digital reputation
Livan, Giacomo; Aste, Tomaso
2016-01-01
The peer-to-peer (P2P) economy relies on establishing trust in distributed networked systems, where the reliability of a user is assessed through digital peer-review processes that aggregate ratings into reputation scores. Here we present evidence of a network effect which biases the digital reputations of the users of P2P networks, showing that P2P networks display exceedingly high levels of reciprocity. In fact, these are so large that they are close to the highest levels structurally compatible with the networks' reputation landscape. This shows that the crowdsourcing process underpinning digital reputation is significantly distorted by the attempt of users to mutually boost reputation, or to retaliate, through the exchange of ratings. We show that the least active users are predominantly responsible for such reciprocity-induced bias, and that this fact can be exploited to suppress the bias itself.
Learning biases predict a word order universal.
Culbertson, Jennifer; Smolensky, Paul; Legendre, Géraldine
2012-03-01
How recurrent typological patterns, or universals, emerge from the extensive diversity found across the world's languages constitutes a central question for linguistics and cognitive science. Recent challenges to a fundamental assumption of generative linguistics-that universal properties of the human language acquisition faculty constrain the types of grammatical systems which can occur-suggest the need for new types of empirical evidence connecting typology to biases of learners. Using an artificial language learning paradigm in which adult subjects are exposed to a mix of grammatical systems (similar to a period of linguistic change), we show that learners' biases mirror a word-order universal, first proposed by Joseph Greenberg, which constrains typological patterns of adjective, numeral, and noun ordering. We briefly summarize the results of a probabilistic model of the hypothesized biases and their effect on learning, and discuss the broader implications of the results for current theories of the origins of cross-linguistic word-order preferences. PMID:22208785
Recognition bias and the physical attractiveness stereotype.
Rohner, Jean-Christophe; Rasmussen, Anders
2012-06-01
Previous studies have found a recognition bias for information consistent with the physical attractiveness stereotype (PAS), in which participants believe that they remember that attractive individuals have positive qualities and that unattractive individuals have negative qualities, regardless of what information actually occurred. The purpose of this research was to examine whether recognition bias for PAS congruent information is replicable and invariant across a variety of conditions (i.e. generalizable). The effects of nine different moderator variables were examined in two experiments. With a few exceptions, the effect of PAS congruence on recognition bias was independent of the moderator variables. The results suggest that the tendency to believe that one remembers information consistent with the physical attractiveness stereotype is a robust phenomenon. PMID:22416805
Recognition bias and the physical attractiveness stereotype.
Rohner, Jean-Christophe; Rasmussen, Anders
2012-06-01
Previous studies have found a recognition bias for information consistent with the physical attractiveness stereotype (PAS), in which participants believe that they remember that attractive individuals have positive qualities and that unattractive individuals have negative qualities, regardless of what information actually occurred. The purpose of this research was to examine whether recognition bias for PAS congruent information is replicable and invariant across a variety of conditions (i.e. generalizable). The effects of nine different moderator variables were examined in two experiments. With a few exceptions, the effect of PAS congruence on recognition bias was independent of the moderator variables. The results suggest that the tendency to believe that one remembers information consistent with the physical attractiveness stereotype is a robust phenomenon.
Racial bias in perceptions of others' pain.
Directory of Open Access Journals (Sweden)
Sophie Trawalter
Full Text Available The present work provides evidence that people assume a priori that Blacks feel less pain than do Whites. It also demonstrates that this bias is rooted in perceptions of status and the privilege (or hardship status confers, not race per se. Archival data from the National Football League injury reports reveal that, relative to injured White players, injured Black players are deemed more likely to play in a subsequent game, possibly because people assume they feel less pain. Experiments 1-4 show that White and Black Americans-including registered nurses and nursing students-assume that Black people feel less pain than do White people. Finally, Experiments 5 and 6 provide evidence that this bias is rooted in perceptions of status, not race per se. Taken together, these data have important implications for understanding race-related biases and healthcare disparities.
Skill-Biased Technological Change in Denmark
DEFF Research Database (Denmark)
Malchow-Møller, Nikolaj; Rose Skaksen, Jan
2003-01-01
Skill-Biased Technological Change in Denmark:A Disaggregate Perspective@*In this paper, we provide an industry-level analysis of skill-biased technological change(SBTC) in Denmark over the last two decades. The analysis shows that SBTC has variedconsiderably across industries, and traditionally...... large Danish industries have experiencedrelatively less SBTC. This may partly explain why wage inequality between skilled and lessskilled has risen less in Denmark than in other countries. We also find that SBTC has beenconcentrated in already skill-intensive industries. This contains important...... information aboutfuture labour requirements, as the relative importance of these industries must be expectedto grow, thereby reinforcing the shift in demand for skilled labour.JEL Classification: J24, J31, L6Keywords: skill-biased technological change, Danish industries...
Cosmology of biased discrete symmetry breaking
Gelmini, Graciela B.; Gleiser, Marcelo; Kolb, Edward W.
1988-01-01
The cosmological consequences of spontaneous breaking of an approximate discrete symmetry are studied. The breaking leads to formation of proto-domains of false and true vacuum separated by domain walls of thickness determined by the mass scale of the model. The cosmological evolution of the walls is extremely sensitive to the magnitude of the biasing; several scenarios are possible, depending on the interplay between the surface tension on the walls and the volume pressure from the biasing. Walls may disappear almost immediately after they form, or may live long enough to dominate the energy density of the Universe and cause power-law inflation. Limits are obtained on the biasing that characterizes each possible scenario.
Motion, identity and the bias toward agency
Directory of Open Access Journals (Sweden)
Chris eFields
2014-08-01
Full Text Available The well-documented human bias toward agency as a cause and therefore an explanation of observed events is typically attributed to evolutionary selection for a social brain. Based on a review of developmental and adult behavioral and neurocognitive data, it is argued that the bias toward agency is a result of the default human solution, developed during infancy, to the computational requirements of object re-identification over gaps in observation of more than a few seconds. If this model is correct, overriding the bias toward agency to construct mechanistic explanations of observed events requires structure-mapping inferences, implemented by the pre-motor action planning system, that replace agents with mechanisms as causes of unobserved changes in contextual or featural properties of objects. Experiments that would test this model are discussed.
Observational biases in flux magnification measurements
Hildebrandt, Hendrik
2015-01-01
Flux magnification is an interesting complement to shear-based lensing measurements, especially at high redshift where sources are harder to resolve. One measures either changes in the source density (magnification bias) or in the shape of the flux distribution (e.g. magnitude-shift). The interpretation of these measurements relies on theoretical estimates of how the observables change under magnification. Here we present simulations to create multi-band photometric mock catalogues of Lyman-break galaxies in a CFHTLenS-like survey that include several observational effects that can change these relations, making simple theoretical estimates unusable. In particular, we show how the magnification bias can be affected by photometric noise, colour selection, and dust extinction. We find that a simple measurement of the slope of the number-counts is not sufficient for the precise interpretation of virtually all observations of magnification bias. We also explore how sensitive the shift in the mean magnitude of a s...
UN Data: Environment Statistics: Waste
World Wide Human Geography Data Working Group — The Environment Statistics Database contains selected water and waste statistics by country. Statistics on water and waste are based on official statistics supplied...
UN Data- Environmental Statistics: Waste
World Wide Human Geography Data Working Group — The Environment Statistics Database contains selected water and waste statistics by country. Statistics on water and waste are based on official statistics supplied...
Grandfather regulations, new source bias, and state air toxics regulations
International Nuclear Information System (INIS)
This paper uses plant-level data from the Census of Manufactures and the variation in toxic air pollution regulations across states to measure the effects of laws that are more stringent for new sources of pollution than for existing sources (so-called 'grandfather' regulations). Of particular interest is the resulting 'new source bias' and its effects on capital vintage and investment. Two industries are examined: commercial printing, which has a local product market; and paint manufacturing, which has a more national market. In general, there seem to be no statistically significant differences in capital vintage or investment between plants in states that grandfather new sources of pollution, plants in states that have no air toxics regulations, and plants in states that regulate both new and existing sources
Lensing Bias to CMB Measurements of Compensated Isocurvature Perturbations
Heinrich, Chen He; Hu, Wayne
2016-01-01
Compensated isocurvature perturbations (CIPs) are modes in which the baryon and dark matter density fluctuations cancel. They arise in the curvaton scenario as well as some models of baryogenesis. While they leave no observable effects on the cosmic microwave background (CMB) at linear order, they do spatially modulate two-point CMB statistics and can be reconstructed in a manner similar to gravitational lensing. Due to the similarity between the effects of CMB lensing and CIPs, lensing contributes nearly Gaussian random noise to the CIP estimator that approximately doubles the reconstruction noise power. Additionally, the cross correlation between lensing and the integrated Sachs-Wolfe (ISW) effect generates a correlation between the CIP estimator and the temperature field even in the absence of a correlated CIP signal. For cosmic-variance limited temperature measurements out to multipoles $l \\leq 2500$, subtracting a fixed lensing bias degrades the detection threshold for CIPs by a factor of $1.3$, whether ...
Bias modulated scanning ion conductance microscopy.
McKelvey, Kim; Perry, David; Byers, Joshua C; Colburn, Alex W; Unwin, Patrick R
2014-04-01
Nanopipets are versatile tools for nanoscience, particularly when used in scanning ion conductance microscopy (SICM) to determine, in a noncontact manner, the topography of a sample. We present a new method, applying an oscillating bias between a quasi-reference counter electrode (QRCE) in the SICM nanopipet probe and a second QRCE in the bulk solution, to generate a feedback signal to control the distance between the end of a nanopipet and a surface. Both the amplitude and phase of the oscillating ion current, induced by the oscillating bias and extracted using a phase-sensitive detector, are shown to be sensitive to the probe-surface distance and are used to provide stable feedback signals. The phase signal is particularly sensitive at high frequencies of the oscillating bias (up to 30 kHz herein). This development eliminates the need to physically oscillate the probe to generate an oscillating ion current feedback signal, as needed for conventional SICM modes. Moreover, bias modulation allows a feedback signal to be generated without any net ion current flow, ensuring that any polarization of the quasi reference counter electrodes, electro-osmotic effects, and perturbations of the supporting electrolyte composition are minimized. Both feedback signals, magnitude and phase, are analyzed through approach curve measurements to different surfaces at a range of distinct frequencies and via impedance measurements at different distances from a surface. The bias modulated response is readily understood via a simple equivalent circuit model. Bias modulated (BM)-SICM is compared to conventional SICM imaging through measurements of substrates with distinct topographical features and yields equivalent results. Finally, BM-SICM with both amplitude and phase feedback is used for topographical imaging of subtle etch features in a calcite crystal surface. The 2 modes yield similar results, but phase-detection opens up the prospect of faster imaging.
CMS Statistics Reference Booklet
U.S. Department of Health & Human Services — The annual CMS Statistics reference booklet provides a quick reference for summary information about health expenditures and the Medicare and Medicaid health...
Playing at Statistical Mechanics
Clark, Paul M.; And Others
1974-01-01
Discussed are the applications of counting techniques of a sorting game to distributions and concepts in statistical mechanics. Included are the following distributions: Fermi-Dirac, Bose-Einstein, and most probable. (RH)
Statistics in Atmospheric Science
Solow, Andrew R.
2003-01-01
This paper reviews the use of statistical methods in atmospheric science. The applications covered include the development, assessment and use of numerical physical models of the atmosphere and more empirical analysis unconnected to physical models.
Cox, D R
2007-01-01
The main phases of applied statistical work are discussed in general terms. The account starts with the clarification of objectives and proceeds through study design, measurement and analysis to interpretation. An attempt is made to extract some general notions.
LBVs and Statistical Inference
Davidson, Kris; Weis, Kerstin
2016-01-01
Smith and Tombleson (2015) asserted that statistical tests disprove the standard view of LBVs, and proposed a far more complex scenario to replace it. But Humphreys et al. (2016) showed that Smith and Tombleson's Magellanic "LBV" sample was a mixture of physically different classes of stars, and genuine LBVs are in fact statistically consistent with the standard view. Smith (2016) recently objected at great length to this result. Here we note that he misrepresented some of the arguments, altered the test criteria, ignored some long-recognized observational facts, and employed inadequate statistical procedures. This case illustrates the dangers of uncareful statistical sampling, as well as the need to be wary of unstated assumptions.
Statistics For Neuroscientists
Directory of Open Access Journals (Sweden)
Subbakrishna D.K
2000-01-01
Full Text Available The role statistical methods play in medicine in the interpretation of empirical data is well recognized by researchers. With modern computing facilities and software packages there is little need for familiarity with the computational details of statistical calculations. However, for the researcher to understand whether these calculations are valid and appropriate it is necessary that the user is aware of the rudiments of the statistical methodology. Also, it needs to be emphasized that no amount of advanced analysis can be a substitute for a properly planned and executed study. An attempt is made in this communication to discuss some of the theoretical issues that are important for the valid analysis and interpretation of precious date that are gathered. The article summarises some of the basic statistical concepts followed by illustrations from live data generated from various research projects from the department of Neurology of this Institute.
Statistical mechanics of superconductivity
Kita, Takafumi
2015-01-01
This book provides a theoretical, step-by-step comprehensive explanation of superconductivity for undergraduate and graduate students who have completed elementary courses on thermodynamics and quantum mechanics. To this end, it adopts the unique approach of starting with the statistical mechanics of quantum ideal gases and successively adding and clarifying elements and techniques indispensible for understanding it. They include the spin-statistics theorem, second quantization, density matrices, the Bloch–De Dominicis theorem, the variational principle in statistical mechanics, attractive interaction, and bound states. Ample examples of their usage are also provided in terms of topics from advanced statistical mechanics such as two-particle correlations of quantum ideal gases, derivation of the Hartree–Fock equations, and Landau’s Fermi-liquid theory, among others. With these preliminaries, the fundamental mean-field equations of superconductivity are derived with maximum mathematical clarity based on ...
... Registry Learn About NF Facts & Statistics NF1 NF2 Schwannomatosis About Us Foundation News & Events Employment Opportunities About ... classified into three distinct types; NF1, NF2 and schwannomatosis. They are caused by different genes, located on ...
Ehrlichiosis: Statistics and Epidemiology
... a tick Diseases transmitted by ticks Statistics and Epidemiology Recommend on Facebook Tweet Share Compartir On this ... Holman RC, McQuiston JH, Krebs JW, Swerdlow DL. Epidemiology of human ehrlichiosis and anaplasmosis in the United ...
Anaplasmosis: Statistics and Epidemiology
... a tick Diseases transmitted by ticks Statistics and Epidemiology Recommend on Facebook Tweet Share Compartir On this ... Holman RC, McQuiston JH, Krebs JW, Swerdlow DL. Epidemiology of human ehrlichiosis and anaplasmosis in the United ...
U.S. Department of Health & Human Services — The United States Cancer Statistics (USCS) online databases in WONDER provide cancer incidence and mortality data for the United States for the years since 1999, by...
Probability and Statistical Inference
Prosper, Harrison B.
2006-01-01
These lectures introduce key concepts in probability and statistical inference at a level suitable for graduate students in particle physics. Our goal is to paint as vivid a picture as possible of the concepts covered.
Richfield, Jon; bookfeller
2016-07-01
In reply to Ralph Kenna and Pádraig Mac Carron's feature article “Maths meets myths” in which they describe how they are using techniques from statistical physics to characterize the societies depicted in ancient Icelandic sagas.
Information theory and statistics
Kullback, Solomon
1997-01-01
Highly useful text studies logarithmic measures of information and their application to testing statistical hypotheses. Includes numerous worked examples and problems. References. Glossary. Appendix. 1968 2nd, revised edition.
Harrison, JM; Robbins, JM; 10.1098/rspa.2010.0254
2011-01-01
Quantum graphs are commonly used as models of complex quantum systems, for example molecules, networks of wires, and states of condensed matter. We consider quantum statistics for indistinguishable spinless particles on a graph, concentrating on the simplest case of abelian statistics for two particles. In spite of the fact that graphs are locally one-dimensional, anyon statistics emerge in a generalized form. A given graph may support a family of independent anyon phases associated with topologically inequivalent exchange processes. In addition, for sufficiently complex graphs, there appear new discrete-valued phases. Our analysis is simplified by considering combinatorial rather than metric graphs -- equivalently, a many-particle tight-binding model. The results demonstrate that graphs provide an arena in which to study new manifestations of quantum statistics. Possible applications include topological quantum computing, topological insulators, the fractional quantum Hall effect, superconductivity and molec...
Gumbel, E J
2012-01-01
This classic text covers order statistics and their exceedances; exact distribution of extremes; the 1st asymptotic distribution; uses of the 1st, 2nd, and 3rd asymptotes; more. 1958 edition. Includes 44 tables and 97 graphs.
Müller-Kirsten, Harald J W
2013-01-01
Statistics links microscopic and macroscopic phenomena, and requires for this reason a large number of microscopic elements like atoms. The results are values of maximum probability or of averaging. This introduction to statistical physics concentrates on the basic principles, and attempts to explain these in simple terms supplemented by numerous examples. These basic principles include the difference between classical and quantum statistics, a priori probabilities as related to degeneracies, the vital aspect of indistinguishability as compared with distinguishability in classical physics, the differences between conserved and non-conserved elements, the different ways of counting arrangements in the three statistics (Maxwell-Boltzmann, Fermi-Dirac, Bose-Einstein), the difference between maximization of the number of arrangements of elements, and averaging in the Darwin-Fowler method. Significant applications to solids, radiation and electrons in metals are treated in separate chapters, as well as Bose-Eins...
Grégoire, G.
2016-05-01
This chapter is devoted to two objectives. The first one is to answer the request expressed by attendees of the first Astrostatistics School (Annecy, October 2013) to be provided with an elementary vademecum of statistics that would facilitate understanding of the given courses. In this spirit we recall very basic notions, that is definitions and properties that we think sufficient to benefit from courses given in the Astrostatistical School. Thus we give briefly definitions and elementary properties on random variables and vectors, distributions, estimation and tests, maximum likelihood methodology. We intend to present basic ideas in a hopefully comprehensible way. We do not try to give a rigorous presentation, and due to the place devoted to this chapter, can cover only a rather limited field of statistics. The second aim is to focus on some statistical tools that are useful in classification: basic introduction to Bayesian statistics, maximum likelihood methodology, Gaussian vectors and Gaussian mixture models.
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...
... Websites About Us Information For... Media Policy Makers Data & Statistics Recommend on Facebook Tweet Share Compartir Sickle ... with sickle cell disease (SCD) by matching up data from studies that monitor all people with SCD ...
Medicaid Drug Claims Statistics
U.S. Department of Health & Human Services — The Medicaid Drug Claims Statistics CD is a useful tool that conveniently breaks up Medicaid claim counts and separates them by quarter and includes an annual count.
U.S. Department of Health & Human Services — This section contains statistical information and reports related to the percentage of electronic transactions being sent to Medicare contractors in the formats...
Williams, Paige; Kern, Margaret L; Waters, Lea
2016-01-01
Employee psychological capital (PsyCap), perceptions of organizational virtue (OV), and work happiness have been shown to be associated within and over time. This study examines selective exposure and confirmation bias as potential processes underlying PsyCap, OV, and work happiness associations. As part of a quasi-experimental study design, school staff (N = 69) completed surveys at three time points. After the first assessment, some staff (n = 51) completed a positive psychology training intervention. Results of descriptive statistics, correlation, and regression analyses on the intervention group provide some support for selective exposure and confirmation bias as explanatory mechanisms. In focusing on the processes through which employee attitudes may influence work happiness this study advances theoretical understanding, specifically of selective exposure and confirmation bias in a field study context.
Zero-Variance Zero-Bias Principle for Observables in quantum Monte Carlo: Application to Forces
Assaraf, R
2003-01-01
A simple and stable method for computing accurate expectation values of observable with Variational Monte Carlo (VMC) or Diffusion Monte Carlo (DMC) algorithms is presented. The basic idea consists in replacing the usual ``bare'' estimator associated with the observable by an improved or ``renormalized'' estimator. Using this estimator more accurate averages are obtained: Not only the statistical fluctuations are reduced but also the systematic error (bias) associated with the approximate VMC or (fixed-node) DMC probability densities. It is shown that improved estimators obey a Zero-Variance Zero-Bias (ZVZB) property similar to the usual Zero-Variance Zero-Bias property of the energy with the local energy as improved estimator. Using this property improved estimators can be optimized and the resulting accuracy on expectation values may reach the remarkable accuracy obtained for total energies. As an important example, we present the application of our formalism to the computation of forces in molecular system...
Williams, Paige; Kern, Margaret L; Waters, Lea
2016-01-01
Employee psychological capital (PsyCap), perceptions of organizational virtue (OV), and work happiness have been shown to be associated within and over time. This study examines selective exposure and confirmation bias as potential processes underlying PsyCap, OV, and work happiness associations. As part of a quasi-experimental study design, school staff (N = 69) completed surveys at three time points. After the first assessment, some staff (n = 51) completed a positive psychology training intervention. Results of descriptive statistics, correlation, and regression analyses on the intervention group provide some support for selective exposure and confirmation bias as explanatory mechanisms. In focusing on the processes through which employee attitudes may influence work happiness this study advances theoretical understanding, specifically of selective exposure and confirmation bias in a field study context. PMID:27378978
Trigger monitoring and rate predictions using Enhanced Bias data from the ATLAS Detector at the LHC
The ATLAS collaboration
2016-01-01
A data-driven method for performing offline rate and CPU usage predictions for any algorithmic selection in the ATLAS High Level Trigger at the Large Hadron Collider is described. To assure statistical sensitivity in the most relevant kinematic regions, a mix of events is selected by the Level 1 trigger system that emphasises higher energies and object multiplicities. This sample, referred to as `enhanced bias', is constructed in such a way that the selection bias is removable with event weights. The use of enhanced bias data to calculate the rates of HLT trigger chains along with complex combinations such as group rates, the total rate and unique rates is described, along with methods for performing extrapolations of rates to different instantaneous luminosities and for performing predictions of trigger CPU usage. The process by which ATLAS collects and processes monitoring data in the High Level Trigger is outlined, this allows for CPU and readout system resource utilisation within the trigger to be studied...
Directory of Open Access Journals (Sweden)
Mahmood Yahyazadehfar
2012-11-01
Full Text Available The purpose of this study is investigating the Status Quo Bias (SQB from suggested biases in behavioral finance. People who are subject to a SQB tend to choose an alternative that was chosen previously (i.e., their status quo even if it is not the optimal choice any more. Status quo bias existence was investigated in this study using Ruenzi and Kempf (2005 model among investment companies listed in Tehran's Stock Exchange during 2003-2010. The data is collected quarterly from investment companies. Also, Stata10.0 software package is used for statistical analysis. The result shows the existence of a SQB is not found in Tehran Stock Exchange
Relative Age Effect in Elite Sports: Methodological Bias or Real Discrimination?
Delorme, Nicolas; Raspaud, Michel; 10.1080/17461390903271584
2010-01-01
Sport sciences researchers talk about a relative age effect when they observe a biased distribution of elite athletes' birthdates, with an over-representation of those born at the beginning of the competitive year and an under-representation of those born at the end. Using the whole sample of the French male licensed soccer players (n = 1,831,524), our study suggests that there could be an important bias in the statistical test of this effect. This bias could in turn lead to falsely conclude to a systemic discrimination in the recruitment of professional players. Our findings question the accuracy of past results concerning the existence of this effect at the elite level.
Traders, Courts and the Home Bias Puzzle
Turrini, Alessandro; Van Ypersele, Tanguy
2001-01-01
Recent evidence shows that the ‘home bias puzzle’ in international trade may be associated with the mere presence of national borders (McCallum (1995)). In this Paper we provide a theoretical framework to explain why borders may matter so much for trade. Our argument is that even between perfectly integrated and similar countries the legal system differs, so that legal costs are higher when business is done abroad. Using a matching model of trade, we show that the home bias is associated with...
Optimal design of APD biasing circuit
Institute of Scientific and Technical Information of China (English)
SUN Chun-sheng; QIN Shi-qiao; WANG Xing-shu; ZHU Dong-hua
2007-01-01
This paper proposes a control method for avalanche photodiode (APD) reverse bias with temperature compensation and load resistance compensation. The influence of background light and load resistance on APD detection circuit is analyzed in detail. A theoretical model of temperature compensation and load resistance compensation is established, which is used for APD biasing circuit designing. It is predicted that this control method is especially suitable for LD laser range finder used on vehicles. Experimental results confirm thatthe design proposed in this paper can considerablely improve the performance of range finder.
Terahertz Bloch oscillator with a modulated bias.
Hyart, Timo; Alexeeva, Natalia V; Mattas, Jussi; Alekseev, Kirill N
2009-04-10
Electrons performing Bloch oscillations in an energy band of a dc-biased superlattice in the presence of weak dissipation can potentially generate THz fields at room temperature. The realization of such a Bloch oscillator is a long-standing problem due to the instability of a homogeneous electric field in conditions of negative differential conductivity. We establish the theoretical feasibility of stable THz gain in a long superlattice device in which the bias is quasistatically modulated by microwave fields. The modulation waveforms must have at least two harmonics in their spectra.
BIAS GENDER: MASALAH UTAMA DALAM INTERPRETASI ARKEOLOGI
Directory of Open Access Journals (Sweden)
Mimi Savitri
2007-06-01
Full Text Available Gender bias is an important theme in Gender Archaeology. It is influenced by modern people thinking and it has influenced archaeological interpretation for a long time. As a result, archaeological interpretation of past society is not objective. This problem should be solved to reach an objective interpretation of people’s life in the past. The author argues that gender bias in archaeology can be solved by actively criticizing androcentrism and paying more attention to men and women’s relationship in the past.
Statistical Engine Knock Control
DEFF Research Database (Denmark)
Stotsky, Alexander A.
2008-01-01
A new statistical concept of the knock control of a spark ignition automotive engine is proposed . The control aim is associated with the statistical hy pothesis test which compares the threshold value to the average value of the max imal amplitud e of the knock sensor signal at a given freq uency...... which includ es generation of the amplitud e signals, a threshold value d etermination and a knock sound mod el is d eveloped for evaluation of the control concept....
Introductory statistical inference
Mukhopadhyay, Nitis
2014-01-01
This gracefully organized text reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, figures, tables, and computer simulations to develop and illustrate concepts. Drills and boxed summaries emphasize and reinforce important ideas and special techniques.Beginning with a review of the basic concepts and methods in probability theory, moments, and moment generating functions, the author moves to more intricate topics. Introductory Statistical Inference studies multivariate random variables, exponential families of dist
Business statistics I essentials
Clark, Louise
2014-01-01
REA's Essentials provide quick and easy access to critical information in a variety of different fields, ranging from the most basic to the most advanced. As its name implies, these concise, comprehensive study guides summarize the essentials of the field covered. Essentials are helpful when preparing for exams, doing homework and will remain a lasting reference source for students, teachers, and professionals. Business Statistics I includes descriptive statistics, introduction to probability, probability distributions, sampling and sampling distributions, interval estimation, and hypothesis t
INTRODUCTION TO NEUTROSOPHIC STATISTICS
Smarandache, Florentin
2014-01-01
Neutrosophic Statistics means statistical analysis of population or sample that has indeterminate (imprecise, ambiguous, vague, incomplete, unknown) data. For example, the population or sample size might not be exactly determinate because of some individuals that partially belong to the population or sample, and partially they do not belong, or individuals whose appurtenance is completely unknown. Also, there are population or sample individuals whose data could be indeterminate. In this book...
Feigelson, Eric D.
2009-01-01
Perhaps more than other physical sciences, astronomy is frequently statistical in nature. The objects under study are inaccessible to direct manipulation in the laboratory, so the astronomer is restricted to observing a few external characteristics and inferring underlying properties and physics. Astronomy played a profound role in the historical development of statistics from the ancient Greeks through the 19th century. But the fields drifted apart in the 20th century as astronomy turned tow...
Johnson, Norman
This is author-approved bcc: This is the third volume of a collection of seminal papers in the statistical sciences written during the past 110 years. These papers have each had an outstanding influence on the development of statistical theory and practice over the last century. Each paper is preceded by an introduction written by an authority in the field providing background information and assessing its influence. Volume III concerntrates on articles from the 1980's while including some earlier articles not included in Volume I and II. Samuel Kotz is Professor of Statistics in the College of Business and Management at the University of Maryland. Norman L. Johnson is Professor Emeritus of Statistics at the University of North Carolina. Also available: Breakthroughs in Statistics Volume I: Foundations and Basic Theory Samuel Kotz and Norman L. Johnson, Editors 1993. 631 pp. Softcover. ISBN 0-387-94037-5 Breakthroughs in Statistics Volume II: Methodology and Distribution Samuel Kotz and Norman L. Johnson, Edi...
Weak lensing statistics from the Coyote Universe
Eifler, Tim
2010-01-01
Analyzing future weak lensing data sets from KIDS, DES, LSST, Euclid, WFIRST requires precise predictions for the weak lensing measures. In this paper we present a weak lensing prediction code based on the Coyote Universe emulator. The Coyote Universe emulator predicts the (non-linear) power spectrum of density fluctuations (P_delta) to high accuracy for k \\in [0.002;3.4] h/Mpc within the redshift interval z \\in [0;1], outside this regime we extend P_delta using a modified Halofit code. This pipeline is used to calculate various second-order cosmic shear statistics, e.g., shear power spectrum, shear-shear correlation function, ring statistics and COSEBIs (Complete Orthogonal Set of EB-mode Integrals), and we examine how the upper limit in k (and z) to which P_delta is known, impacts on these statistics. For example, we find that k_max~8 h/Mpc causes a bias in the shear power spectrum at l~4000 that is comparable to the statistical errors (intrinsic shape-noise and cosmic variance) of a DES-like survey, wherea...
Attention Bias Variability and Symptoms of Posttraumatic Stress Disorder
Iacoviello, Brian M.; Wu, Gang; Abend, Rany; Murrough, James W.; Feder, Adriana; Fruchter, Eyal; Levinstein, Yoav; Wald, Ilan; Bailey, Christopher R.; Pine, Daniel S.; Neumeister, Alexander; Bar-Haim, Yair; Charney, Dennis S.
2014-01-01
Cognitive theories implicate information-processing biases in the etiology of anxiety disorders. Results of attention-bias studies in posttraumatic stress disorder (PTSD) have been inconsistent, suggesting biases towards and away from threat. Within-subject variability of attention biases in posttraumatic patients may be a useful marker for attentional control impairment and the development of posttrauma symptoms. This study reports 2 experiments investigating threat-related attention biases,...
The influence of cognitive biases on psychophysiological vulnerability to stress
Randall, Kate
2012-01-01
Individuals who disproportionately attend to negative aspects of a situation (attention bias), or who unduly interpret ambiguity in a negative manner (interpretive bias) report more psychological ill-effects of stress than those with balanced or positively-skewed inclinations. Cognitive Bias Modification (CBM) techniques improve maladaptive biases through implicitly-based association learning, with induced positive biases buffering the future perception of stress. Six experimen...
Directory of Open Access Journals (Sweden)
Alexander Miloff
2015-09-01
Full Text Available Social anxiety disorder (SAD and attentional bias are theoretically connected in cognitive behavioral therapeutic models. In fact, there is an emerging field focusing on modifying attentional bias as a stand-alone treatment. However, it is unclear to what degree these attentional biases are present before commencing treatment. The purpose of this study was to measure pre-treatment attentional bias in 153 participants diagnosed with SAD using a home-based Internet version of the dot-probe paradigm. Results showed no significant correlation for attentional bias (towards or away from negative words or faces and the self-rated version of the Liebowitz Social Anxiety Scale (LSAS-SR. However, two positive correlations were found for the secondary measures Generalized Anxiety Disorder 7 (GAD-7 and Patient Health Questionnaire 9 (PHQ-9. These indicated that those with elevated levels of anxiety and depression had a higher bias towards negative faces in neutral–negative and positive–negative valence combinations, respectively. The unreliability of the dot-probe paradigm and home-based Internet delivery are discussed to explain the lack of correlations between LSAS-SR and attentional bias. Changes to the dot-probe task are suggested that could improve reliability.
Bias in emerging biomarkers for bipolar disorder
DEFF Research Database (Denmark)
Carvalho, A F; Köhler, C A; Fernandes, B S;
2016-01-01
BACKGROUND: To date no comprehensive evaluation has appraised the likelihood of bias or the strength of the evidence of peripheral biomarkers for bipolar disorder (BD). Here we performed an umbrella review of meta-analyses of peripheral non-genetic biomarkers for BD. METHOD: The Pubmed...
Exchange bias mediated by interfacial nanoparticles (invited)
Energy Technology Data Exchange (ETDEWEB)
Berkowitz, A. E., E-mail: aberk@ucsd.edu [Department of Physics, University of California, San Diego, La Jolla, California 92093 (United States); Center for Magnetic Recording Research, University of California, California 92093 (United States); Sinha, S. K. [Department of Physics, University of California, San Diego, La Jolla, California 92093 (United States); Fullerton, E. E. [Center for Magnetic Recording Research, University of California, California 92093 (United States); Smith, D. J. [Department of Physics, Arizona State University, Tempe, Arizona 85287 (United States)
2015-05-07
The objective of this study on the iconic exchange-bias bilayer Permalloy/CoO has been to identify those elements of the interfacial microstructure and accompanying magnetic properties that are responsible for the exchange-bias and hysteretic properties of this bilayer. Both epitaxial and polycrystalline samples were examined. X-ray and neutron reflectometry established that there existed an interfacial region, of width ∼1 nm, whose magnetic properties differed from those of Py or CoO. A model was developed for the interfacial microstructure that predicts all the relevant properties of this system; namely; the temperature and Permalloy thickness dependence of the exchange-bias, H{sub EX}, and coercivity, H{sub C}; the much smaller measured values of H{sub EX} from what was nominally expected; the different behavior of H{sub EX} and H{sub C} in epitaxial and polycrystalline bilayers. A surprising result is that the exchange-bias does not involve direct exchange-coupling between Permalloy and CoO, but rather is mediated by CoFe{sub 2}O{sub 4} nanoparticles in the interfacial region.
Jackknife bias reduction for polychotomous logistic regression.
Bull, S B; Greenwood, C M; Hauck, W W
1997-03-15
Despite theoretical and empirical evidence that the usual MLEs can be misleading in finite samples and some evidence that bias reduced estimates are less biased and more efficient, they have not seen a wide application in practice. One can obtain bias reduced estimates by jackknife methods, with or without full iteration, or by use of higher order terms in a Taylor series expansion of the log-likelihood to approximate asymptotic bias. We provide details of these methods for polychotomous logistic regression with a nominal categorical response. We conducted a Monte Carlo comparison of the jackknife and Taylor series estimates in moderate sample sizes in a general logistic regression setting, to investigate dichotomous and trichotomous responses and a mixture of correlated and uncorrelated binary and normal covariates. We found an approximate two-step jackknife and the Taylor series methods useful when the ratio of the number of observations to the number of parameters is greater than 15, but we cannot recommend the two-step and the fully iterated jackknife estimates when this ratio is less than 20, especially when there are large effects, binary covariates, or multicollinearity in the covariates.
Knowledge of Social Affiliations Biases Economic Decisions
Martinez, Joel E.; Mack, Michael L.; Gelman, Bernard D.; Preston, Alison R.
2016-01-01
An individual’s reputation and group membership can produce automatic judgments and behaviors toward that individual. Whether an individual’s social reputation impacts interactions with affiliates has yet to be demonstrated. We tested the hypothesis that during initial encounters with others, existing knowledge of their social network guides behavior toward them. Participants learned reputations (cooperate, defect, or equal mix) for virtual players through an iterated economic game (EG). Then, participants learned one novel friend for each player. The critical question was how participants treated the friends in a single-shot EG after the friend-learning phase. Participants tended to cooperate with friends of cooperators and defect on friends of defectors, indicative of a decision making bias based on memory for social affiliations. Interestingly, participants’ explicit predictions of the friends’ future behavior showed no such bias. Moreover, the bias to defect on friends of defectors was enhanced when affiliations were learned in a social context; participants who learned to associate novel faces with player faces during reinforcement learning did not show reputation-based bias for associates of defectors during single-shot EG. These data indicate that when faced with risky social decisions, memories of social connections influence behavior implicitly. PMID:27441563
Vowel bias in Danish word-learning
DEFF Research Database (Denmark)
Højen, Anders; Nazzi, Thierry
2016-01-01
The present study explored whether the phonological bias favoring consonants found in French-learning infants and children when learning new words (Havy & Nazzi, 2009; Nazzi, 2005) is language-general, as proposed by Nespor, Peña and Mehler (2003), or varies across languages, perhaps as a function...
Researching Sex Bias in the Classroom.
Donlan, Dan
This paper outlines five methods of research on sex bias in the classroom: one-time survey, one class/one treatment, two class/two treatment, one class/random assignment to treatment, and analysis of differentiated effect. It shows how each method could be used in attempting to measure the effect of a unit on Norma Klein's "Mom, the Wolfman and…
Bias sensitive multispectral structures for imaging applications
International Nuclear Information System (INIS)
In this paper we present results on the optimization of an pinpii'n' type a-Si:H based three color detector with voltage controlled spectral sensitivity. The sensor element was fabricated on a glass covered with Indium Tin Oxide (ITO) and consists of a p-i-n a-SiC:H multilayer structure which faces the incident illumination, followed by a-SiC:H(-p)/a-SiC:H(-i)/a-Si:H(-i')/a-SiC:H(-n')/ITO heterostructure, that allows the optically addressed readout. Results show that this approach leads to regionally different collection parameters resulting in multispectral photodiodes. In the polychromatic operation mode different sensitivity ranges are programmed by switching between different biases so that the basic colors can be resolved with a single device. Positive bias is needed under blue irradiation and moderated reverse bias under green. The threshold voltage between green and red sensitivity depends on the thickness of the bottom a-SiC:H (-i) layer, and corresponds to the complete confinement of the absorbed green photons across the pinpi sequence. As the thickness of the a-Si:H i'-layer increases, the self-reverse effect due to the front absorption will be balanced by the decrease of the self-forward effect due to the back absorption shifting the threshold voltage to lower reverse bias. The various design parameters are discussed and supported by a 2D numerical simulation
Avoiding bias in safety testing design
DEFF Research Database (Denmark)
Calow, Peter
2011-01-01
All scientists are biased, no matter what their backgrounds or affiliations, so what is it about the scientific method that overcomes this and which makes science so successful? Key features are transparency and critical peer scrutiny. These general issues will be will be considered in terms...
Very Massive Tracers and Higher Derivative Biases
Fujita, Tomohiro; Senatore, Leonardo; Vlah, Zvonimir; Angulo, Raul
2016-01-01
Most of the upcoming cosmological information will come from analyzing the clustering of the Large Scale Structures (LSS) of the universe through LSS or CMB observations. It is therefore essential to be able to understand their behavior with exquisite precision. The Effective Field Theory of Large Scale Structures (EFTofLSS) provides a consistent framework to make predictions for LSS observables in the mildly non-linear regime. In this paper we focus on biased tracers. We argue that in calculations at a given order in the dark matter perturbations, highly biased tracers will underperform because of their larger higher derivative biases. A natural prediction of the EFTofLSS is therefore that by simply adding higher derivative biases, all tracers should perform comparably well. We implement this prediction for the halo-halo and the halo-matter power spectra at one loop, and the halo-halo-halo, halo-halo-matter, and halo-matter-matter bispectra at tree-level, and compare with simulations. We find good agreement ...
Uncovering Racial Bias in Nursing Fundamentals Textbooks.
Byrne, Michelle M.
2001-01-01
The portrayal of African Americans in nursing fundamentals textbooks was analyzed, resulting in 11 themes in the areas of history, culture, and physical assessment. Few African American leaders were included, and racial bias and stereotyping were apparent. Differences were often discussed using Eurocentric norms, and language tended to minimize…
Attentional bias temporal dynamics in remitted depression.
Zvielli, Ariel; Vrijsen, Janna N; Koster, Ernst H W; Bernstein, Amit
2016-08-01
Theory implicates attentional bias (AB) or dysregulated attentional processing of emotional information in the recurrence of major depressive episodes. However, empirical study of AB among remitted depressed patients is limited in scope and has yielded mixed findings. Mixed findings may be accounted for by how the field has conceptualized and thereby studied AB. We propose that a novel temporal dynamic process perspective on AB may help disambiguate extant findings and elucidate the nature of AB in remitted depression. Thus, we reexamined Dot Probe data among remitted depressed patients (RMD; n = 328) and nondepressed controls (NDC; n = 82) that previously yielded null effects when AB was quantified by means of the traditional aggregated mean bias score (Vrijsen et al., 2014). We reanalyzed data using a novel computational approach that extracts a series of bias estimations from trial to trial (Zvielli, Bernstein, & Koster, 2015). Key features of these dynamic process signals revealed moderate to excellent reliability relative to the traditional aggregated mean bias scores. These features of AB dynamics-specifically temporal variability in AB including AB toward and away from emotional stimuli-were significantly elevated among RMDs relative to NDCs. Moreover, among RMDs, a greater number of past depressive episodes were associated with elevation in these features of AB dynamics. Effects were not accounted for by residual depressive symptoms or social anxiety symptoms. Findings indicate that dysregulation in attentional processing of emotional information reflected in AB dynamics may be key to depression vulnerability. (PsycINFO Database Record PMID:27505407
Bias and Obfuscation in Kendler's (2005) "Clarification"
Schneider, Kirk J.
2006-01-01
This paper comments on the article "Psychology and Phenomenology: A Clarification" by H. H. Kendler. In this article, Kendler misrepresented contemporary existential-humanistic psychology and conventional (or natural) scientific psychology. With regard to the former, he presented a confused, unwittingly biased, and all-too-stereotypic picture.…
Bounding the Bias of Contrastive Divergence Learning
DEFF Research Database (Denmark)
Fischer, Anja; Igel, Christian
2011-01-01
number of variables in the RBM, and the maximum change in energy that can be produced by changing a single variable. The last reflects the dependence on the absolute values of the RBM parameters. The magnitude of the bias is also affected by the distance in variation between the modeled distribution and...
Examining Gender Bias in Studies of Innovation
Crowden, N.
2003-01-01
This paper examines the presence of a gender bias in studies of innovation. Using the Innovation Systems Research Network (ISRN) and its interview guide as a case study, this research project examines how accurately and completely such innovation studies present gender differences in the innovation process.
A new polarization amplitude bias reduction method
Vidal, Matias; Leahy, J. P.; Dickinson, C.
2016-09-01
Polarization amplitude estimation is affected by a positive noise bias, particularly important in regions with low signal-to-noise ratio (SNR). We present a new approach to correct for this bias in the case there is additional information about the polarization angle. We develop the `known-angle estimator' that works in the special case when there is an independent and high SNR (≳ 2σ) measurement of the polarization angle. It is derived for the general case where the uncertainties in the Q, U Stokes parameters are not symmetric. This estimator completely corrects for the polarization bias if the polarization angle is perfectly known. In the realistic case, where the angle template has uncertainties, a small residual bias remains, but that is shown to be much smaller that the one left by other classical estimators. We also test our method with more realistic data, using the noise properties of the three lower frequency maps of Wilkinson Microwave Anisotropy Probe. In this case, the known-angle estimator also produces better results than methods that do not include the angle information. This estimator is therefore useful in the case where the polarization angle is expected to be constant over different data sets with different SNR.
Zero bias transformation and asymptotic expansions
Jiao, Ying
2012-01-01
Let W be a sum of independent random variables. We apply the zero bias transformation to deduce recursive asymptotic expansions for $\\mathbb {E}[h(W)]$ in terms of normal expectations, or of Poisson expectations for integer-valued random variables. We also discuss the estimates of remaining errors.
Accounting for discovery bias in genomic prediction
Our objective was to evaluate an approach to mitigating discovery bias in genomic prediction. Accuracy may be improved by placing greater emphasis on regions of the genome expected to be more influential on a trait. Methods emphasizing regions result in a phenomenon known as “discovery bias” if info...
Assessing Projection Bias in Consumers' Food Preferences.
Directory of Open Access Journals (Sweden)
Tiziana de-Magistris
Full Text Available The aim of this study is to test whether projection bias exists in consumers' purchasing decisions for food products. To achieve our aim, we used a non-hypothetical experiment (i.e., experimental auction, where hungry and non-hungry participants were incentivized to reveal their willingness to pay (WTP. The results confirm the existence of projection bias when consumers made their decisions on food products. In particular, projection bias existed because currently hungry participants were willing to pay a higher price premium for cheeses than satiated ones, both in hungry and satiated future states. Moreover, participants overvalued the food product more when they were delivered in the future hungry condition than in the satiated one. Our study provides clear, quantitative and meaningful evidence of projection bias because our findings are based on economic valuation of food preferences. Indeed, the strength of this study is that findings are expressed in terms of willingness to pay which is an interpretable amount of money.
The Specific Bias in Dynamic Monte Carlo Simulations of Nuclear Reactor
Yamamoto, Toshihisa; Endo, Hiroshi; Ishizu, Tomoko; Tatewaki, Isao
2014-06-01
During the development of Monte-Carlo-based dynamic code system, we have encountered two major Monte-Carlo-specific problems. One is the break down due to "false super-criticality" which is caused by an accidentally large eigenvalue due to statistical error in spite of the fact that the reactor is actually not. The other problem, which is the main topic in this paper, is that the statistical error in power level using the reactivity calculated with Monte Carlo code is not symmetric about its mean but always positively biased. This signifies that the bias is accumulated as the calculation proceeds and consequently results in over-estimation of the final power level. It should be noted that the bias will not eliminated by refining time step as long as the variance is not zero. A preliminary investigation on this matter using the one-group-precursor point kinetic equations was made and it was concluded that the bias in power level is approximately proportional to the product of variance in Monte Carlo calculation and elapsed time. This conclusion was verified with some numerical experiments. This outcome is important in quantifying the required precision of the Monte-Carlo-based reactivity calculations.
Audibility and visual biasing in speech perception
Clement, Bart Richard
Although speech perception has been considered a predominantly auditory phenomenon, large benefits from vision in degraded acoustic conditions suggest integration of audition and vision. More direct evidence of this comes from studies of audiovisual disparity that demonstrate vision can bias and even dominate perception (McGurk & MacDonald, 1976). It has been observed that hearing-impaired listeners demonstrate more visual biasing than normally hearing listeners (Walden et al., 1990). It is argued here that stimulus audibility must be equated across groups before true differences can be established. In the present investigation, effects of visual biasing on perception were examined as audibility was degraded for 12 young normally hearing listeners. Biasing was determined by quantifying the degree to which listener identification functions for a single synthetic auditory /ba-da-ga/ continuum changed across two conditions: (1)an auditory-only listening condition; and (2)an auditory-visual condition in which every item of the continuum was synchronized with visual articulations of the consonant-vowel (CV) tokens /ba/ and /ga/, as spoken by each of two talkers. Audibility was altered by presenting the conditions in quiet and in noise at each of three signal-to- noise (S/N) ratios. For the visual-/ba/ context, large effects of audibility were found. As audibility decreased, visual biasing increased. A large talker effect also was found, with one talker eliciting more biasing than the other. An independent lipreading measure demonstrated that this talker was more visually intelligible than the other. For the visual-/ga/ context, audibility and talker effects were less robust, possibly obscured by strong listener effects, which were characterized by marked differences in perceptual processing patterns among participants. Some demonstrated substantial biasing whereas others demonstrated little, indicating a strong reliance on audition even in severely degraded acoustic
Watanabe, Satoshi; Kanae, Shinjiro; Seto, Shinta; Yeh, Pat J.-F.; Hirabayashi, Yukiko; Oki, Taikan
2012-12-01
Bias-correction methods applied to monthly temperature and precipitation data simulated by multiple General Circulation Models (GCMs) are evaluated in this study. Although various methods have been proposed recently, an intercomparison among them using multiple GCM simulations has seldom been reported. Moreover, no previous methods have addressed the issue how to adequately deal with the changes of the statistics of bias-corrected variables from the historical to future simulations. In this study, a new method which conserves the changes of mean and standard deviation of the uncorrected model simulation data is proposed, and then five previous bias-correction methods as well as the proposed new method are intercompared by applying them to monthly temperature and precipitation data simulated from 12 GCMs in the Coupled Model Intercomparison Project (CMIP3) archives. Parameters of each method are calibrated by using 1948-1972 observed data and validated in the 1974-1998 period. These methods are then applied to the GCM future simulations (2073-2097) and the bias-corrected data are intercompared. For the historical simulations, negligible difference can be found between observed and bias-corrected data. However, the differences in future simulations are large dependent on the characteristics of each method. The new method successfully conserves the changes in the mean, standard deviation and the coefficient of variation before and after bias-correction. The differences of bias-corrected data among methods are discussed according to their respective characteristics. Importantly, this study classifies available correction methods into two distinct categories, and articulates important features for each of them.
Systematic Angle Random Walk Estimation of the Constant Rate Biased Ring Laser Gyro
Directory of Open Access Journals (Sweden)
Guohu Feng
2013-02-01
Full Text Available An actual account of the angle random walk (ARW coefficients of gyros in the constant rate biased rate ring laser gyro (RLG inertial navigation system (INS is very important in practical engineering applications. However, no reported experimental work has dealt with the issue of characterizing the ARW of the constant rate biased RLG in the INS. To avoid the need for high cost precise calibration tables and complex measuring set-ups, the objective of this study is to present a cost-effective experimental approach to characterize the ARW of the gyros in the constant rate biased RLG INS. In the system, turntable dynamics and other external noises would inevitably contaminate the measured RLG data, leading to the question of isolation of such disturbances. A practical observation model of the gyros in the constant rate biased RLG INS was discussed, and an experimental method based on the fast orthogonal search (FOS for the practical observation model to separate ARW error from the RLG measured data was proposed. Validity of the FOS-based method was checked by estimating the ARW coefficients of the mechanically dithered RLG under stationary and turntable rotation conditions. By utilizing the FOS-based method, the average ARW coefficient of the constant rate biased RLG in the postulate system is estimated. The experimental results show that the FOS-based method can achieve high denoising ability. This method estimate the ARW coefficients of the constant rate biased RLG in the postulate system accurately. The FOS-based method does not need precise calibration table with high cost and complex measuring set-up, and Statistical results of the tests will provide us references in engineering application of the constant rate biased RLG INS.
Sippel, S.; Otto, F. E. L.; Forkel, M.; Allen, M. R.; Guillod, B. P.; Heimann, M.; Reichstein, M.; Seneviratne, S. I.; Kirsten, T.; Mahecha, M. D.
2015-12-01
Understanding, quantifying and attributing the impacts of climatic extreme events and variability is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit pronounced biases in their output that hinders any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies most of which have been criticized for physical inconsistency and the non-preservation of the multivariate correlation structure. We assess how biases and their correction affect the quantification and attribution of simulated extremes and variability in i) climatological variables and ii) impacts on ecosystem functioning as simulated by a terrestrial biosphere model. Our study demonstrates that assessments of simulated climatic extreme events and impacts in the terrestrial biosphere are highly sensitive to bias correction schemes with major implications for the detection and attribution of these events. We introduce a novel ensemble-based resampling scheme based on a large regional climate model ensemble generated by the distributed weather@home setup[1], which fully preserves the physical consistency and multivariate correlation structure of the model output. We use extreme value statistics to show that this procedure considerably improves the representation of climatic extremes and variability. Subsequently, biosphere-atmosphere carbon fluxes are simulated using a terrestrial ecosystem model (LPJ-GSI) to further demonstrate the sensitivity of ecosystem impacts to the methodology of bias correcting climate model output. We find that uncertainties arising from bias correction schemes are comparable in magnitude to model structural and parameter uncertainties. The present study consists of a first attempt to alleviate climate model biases in a physically consistent way and demonstrates that this yields improved simulations of
Multivariate Statistical Process Control
DEFF Research Database (Denmark)
Kulahci, Murat
2013-01-01
As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control (SPC) and monitoring for which the aim is to iden......As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control (SPC) and monitoring for which the aim...... is to identify “out-of-control” state of a process using control charts in order to reduce the excessive variation caused by so-called assignable causes. In practice, the most common method of monitoring multivariate data is through a statistic akin to the Hotelling’s T2. For high dimensional data with excessive...... in conjunction with image data are plagued with various challenges beyond the usual ones encountered in current applications. In this presentation we will introduce the basic ideas of SPC and the multivariate control charts commonly used in industry. We will further discuss the challenges the practitioners...
Investigating and correcting plasma DNA sequencing coverage bias to enhance aneuploidy discovery.
Directory of Open Access Journals (Sweden)
Dineika Chandrananda
Full Text Available Pregnant women carry a mixture of cell-free DNA fragments from self and fetus (non-self in their circulation. In recent years multiple independent studies have demonstrated the ability to detect fetal trisomies such as trisomy 21, the cause of Down syndrome, by Next-Generation Sequencing of maternal plasma. The current clinical tests based on this approach show very high sensitivity and specificity, although as yet they have not become the standard diagnostic test. Here we describe improvements to the analysis of the sequencing data by reducing GC bias and better handling of the genomic repeats. We show substantial improvements in the sensitivity of the standard trisomy 21 statistical tests, which we measure by artificially reducing read coverage. We also explore the bias stemming from the natural cleavage of plasma DNA by examining DNA motifs and position specific base distributions. We propose a model to correct this fragmentation bias and observe that incorporating this bias does not lead to any further improvements in the detection of fetal trisomy. The improved bias corrections that we demonstrate in this work can be readily adopted into existing fetal trisomy detection protocols and should also lead to improvements in sub-chromosomal copy number variation detection.
Stochastic bias-correction of daily rainfall scenarios for hydrological applications
Directory of Open Access Journals (Sweden)
I. Portoghese
2011-09-01
Full Text Available The accuracy of rainfall predictions provided by climate models is crucial for the assessment of climate change impacts on hydrological processes. In fact, the presence of bias in downscaled precipitation may produce large bias in the assessment of soil moisture dynamics, river flows and groundwater recharge.
In this study, a comparison between statistical properties of rainfall observations and model control simulations from a Regional Climate Model (RCM was performed through a robust and meaningful representation of the precipitation process. The output of the adopted RCM was analysed and re-scaled exploiting the structure of a stochastic model of the point rainfall process. In particular, the stochastic model is able to adequately reproduce the rainfall intermittency at the synoptic scale, which is one of the crucial aspects for the Mediterranean environments. Possible alteration in the local rainfall regime was investigated by means of the historical daily time-series from a dense rain-gauge network, which were also used for the analysis of the RCM bias in terms of dry and wet periods and storm intensity. The result is a stochastic scheme for bias-correction at the RCM-cell scale, which produces a realistic representation of the daily rainfall intermittency and precipitation depths, though a residual bias in the storm intensity of longer storm events persists.
Fluency and belief bias in deductive reasoning: new indices for old effects.
Trippas, Dries; Handley, Simon J; Verde, Michael F
2014-01-01
Models based on signal detection theory (SDT) have occupied a prominent role in domains such as perception, categorization, and memory. Recent work by Dube et al. (2010) suggests that the framework may also offer important insights in the domain of deductive reasoning. Belief bias in reasoning has traditionally been examined using indices based on raw endorsement rates-indices that critics have claimed are highly problematic. We discuss a new set of SDT indices fit for the investigation belief bias and apply them to new data examining the effect of perceptual disfluency on belief bias in syllogisms. In contrast to the traditional approach, the SDT indices do not violate important statistical assumptions, resulting in a decreased Type 1 error rate. Based on analyses using these novel indices we demonstrate that perceptual disfluency leads to decreased reasoning accuracy, contrary to predictions. Disfluency also appears to eliminate the typical link found between cognitive ability and the effect of beliefs on accuracy. Finally, replicating previous work, we demonstrate that cognitive ability leads to an increase in reasoning accuracy and a decrease in the response bias component of belief bias. PMID:25009515
Fluency and belief bias in deductive reasoning: New indices for old effects
Directory of Open Access Journals (Sweden)
Dries eTrippas
2014-06-01
Full Text Available Models based on signal detection theory (SDT have occupied a prominent role in domains such as perception, categorisation, and memory. Recent work by Dube et al. (2010 suggests that the framework may also offer important insights in the domain of deductive reasoning. Belief bias in reasoning has traditionally been examined using indices based on raw endorsement rates – indices that critics have claimed are highly problematic. We discuss a new set of SDT indices fit for the investigation belief bias and apply them to new data examining the effect of perceptual disfluency on belief bias in syllogisms. In contrast to the traditional approach, the SDT indices do not violate important statistical assumptions, resulting in a decreased Type 1 error rate. Based on analyses using these novel indices we demonstrate that disfluency leads to decreased reasoning accuracy, contrary to predictions. Disfluency also appears to eliminate the typical link found between cognitive ability and the effect of beliefs on accuracy. Finally, replicating previous work, we demonstrate that cognitive ability leads to an increase in reasoning accuracy and a decrease in the response bias component of belief bias.
Investigating and correcting plasma DNA sequencing coverage bias to enhance aneuploidy discovery.
Chandrananda, Dineika; Thorne, Natalie P; Ganesamoorthy, Devika; Bruno, Damien L; Benjamini, Yuval; Speed, Terence P; Slater, Howard R; Bahlo, Melanie
2014-01-01
Pregnant women carry a mixture of cell-free DNA fragments from self and fetus (non-self) in their circulation. In recent years multiple independent studies have demonstrated the ability to detect fetal trisomies such as trisomy 21, the cause of Down syndrome, by Next-Generation Sequencing of maternal plasma. The current clinical tests based on this approach show very high sensitivity and specificity, although as yet they have not become the standard diagnostic test. Here we describe improvements to the analysis of the sequencing data by reducing GC bias and better handling of the genomic repeats. We show substantial improvements in the sensitivity of the standard trisomy 21 statistical tests, which we measure by artificially reducing read coverage. We also explore the bias stemming from the natural cleavage of plasma DNA by examining DNA motifs and position specific base distributions. We propose a model to correct this fragmentation bias and observe that incorporating this bias does not lead to any further improvements in the detection of fetal trisomy. The improved bias corrections that we demonstrate in this work can be readily adopted into existing fetal trisomy detection protocols and should also lead to improvements in sub-chromosomal copy number variation detection.
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
APPLIED BEHAVIORAL FINANCE: INVESTOR BIASES, PERFORMANCE REVERSION TO THE MEAN and TREND FORMATION
Directory of Open Access Journals (Sweden)
ADRIAN MITROI
2014-02-01
Full Text Available In the pursuit of understanding the behavior of the market player, the basic argument relays on the supposition that the risk appetite increases exactly at the worst moment - when the capacity to assume additional risk decreases significantly.People view a sample randomly drawn from a population as highly representative and cvasi similar to the population in all its essential characteristics. They expect any two samples drawn from a particular population to be more similar to one another and to the population than is statistically justifiable. This behavior is different from the tenets of classic finance theory. The paper aims at demonstating that investor psychological biases lead to investment performance to tilt to the mean in the long run and by following the trend, the financial market population do not enjoy significant sustainable benefits. As a reflection of the behavioral biases and influences, the statistical demonstration supports the conclusion that markets do not random walk.
Helping Alleviate Statistical Anxiety with Computer Aided Statistical Classes
Stickels, John W.; Dobbs, Rhonda R.
2007-01-01
This study, Helping Alleviate Statistical Anxiety with Computer Aided Statistics Classes, investigated whether undergraduate students' anxiety about statistics changed when statistics is taught using computers compared to the traditional method. Two groups of students were questioned concerning their anxiety about statistics. One group was taught…
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
Kwon, Oh-Sang; Knill, David C
2013-03-12
Because of uncertainty and noise, the brain should use accurate internal models of the statistics of objects in scenes to interpret sensory signals. Moreover, the brain should adapt its internal models to the statistics within local stimulus contexts. Consider the problem of hitting a baseball. The impoverished nature of the visual information available makes it imperative that batters use knowledge of the temporal statistics and history of previous pitches to accurately estimate pitch speed. Using a laboratory analog of hitting a baseball, we tested the hypothesis that the brain uses adaptive internal models of the statistics of object speeds to plan hand movements to intercept moving objects. We fit Bayesian observer models to subjects' performance to estimate the statistical environments in which subjects' performance would be ideal and compared the estimated statistics with the true statistics of stimuli in an experiment. A first experiment showed that subjects accurately estimated and used the variance of object speeds in a stimulus set to time hitting behavior but also showed serial biases that are suboptimal for stimuli that were uncorrelated over time. A second experiment showed that the strength of the serial biases depended on the temporal correlations within a stimulus set, even when the biases were estimated from uncorrelated stimulus pairs subsampled from the larger set. Taken together, the results show that subjects adapted their internal models of the variance and covariance of object speeds within a stimulus set to plan interceptive movements but retained a bias to positive correlations. PMID:23440185
Energy Technology Data Exchange (ETDEWEB)
NONE
2010-07-01
Detailed, complete, timely and reliable statistics are essential to monitor the energy situation at a country level as well as at an international level. Energy statistics on supply, trade, stocks, transformation and demand are indeed the basis for any sound energy policy decision. For instance, the market of oil -- which is the largest traded commodity worldwide -- needs to be closely monitored in order for all market players to know at any time what is produced, traded, stocked and consumed and by whom. In view of the role and importance of energy in world development, one would expect that basic energy information to be readily available and reliable. This is not always the case and one can even observe a decline in the quality, coverage and timeliness of energy statistics over the last few years.
Probability and Bayesian statistics
1987-01-01
This book contains selected and refereed contributions to the "Inter national Symposium on Probability and Bayesian Statistics" which was orga nized to celebrate the 80th birthday of Professor Bruno de Finetti at his birthplace Innsbruck in Austria. Since Professor de Finetti died in 1985 the symposium was dedicated to the memory of Bruno de Finetti and took place at Igls near Innsbruck from 23 to 26 September 1986. Some of the pa pers are published especially by the relationship to Bruno de Finetti's scientific work. The evolution of stochastics shows growing importance of probability as coherent assessment of numerical values as degrees of believe in certain events. This is the basis for Bayesian inference in the sense of modern statistics. The contributions in this volume cover a broad spectrum ranging from foundations of probability across psychological aspects of formulating sub jective probability statements, abstract measure theoretical considerations, contributions to theoretical statistics an...
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...... that rarely connect concepts to data and books on econometrics and time series analysis that do not cover specific problems related to option valuation. The book discusses applications of financial derivatives pertaining to risk assessment and elimination. The authors cover various statistical...... and mathematical techniques, including linear and nonlinear time series analysis, stochastic calculus models, stochastic differential equations, Itō’s formula, the Black–Scholes model, the generalized method-of-moments, and the Kalman filter. They explain how these tools are used to price financial derivatives...
Suite versus composite statistics
Balsillie, J.H.; Tanner, W.F.
1999-01-01
Suite and composite methodologies, two statistically valid approaches for producing statistical descriptive measures, are investigated for sample groups representing a probability distribution where, in addition, each sample is probability distribution. Suite and composite means (first moment measures) are always equivalent. Composite standard deviations (second moment measures) are always larger than suite standard deviations. Suite and composite values for higher moment measures have more complex relationships. Very seldom, however, are they equivalent, and they normally yield statistically significant but different results. Multiple samples are preferable to single samples (including composites) because they permit the investigator to examine sample-to-sample variability. These and other relationships for suite and composite probability distribution analyses are investigated and reported using granulometric data.
READING STATISTICS AND RESEARCH
Directory of Open Access Journals (Sweden)
Reviewed by Yavuz Akbulut
2008-10-01
Full Text Available The book demonstrates the best and most conservative ways to decipher and critique research reports particularly for social science researchers. In addition, new editions of the book are always better organized, effectively structured and meticulously updated in line with the developments in the field of research statistics. Even the most trivial issues are revisited and updated in new editions. For instance, purchaser of the previous editions might check the interpretation of skewness and kurtosis indices in the third edition (p. 34 and in the fifth edition (p.29 to see how the author revisits every single detail. Theory and practice always go hand in hand in all editions of the book. Re-reading previous editions (e.g. third edition before reading the fifth edition gives the impression that the author never stops ameliorating his instructional text writing methods. In brief, “Reading Statistics and Research” is among the best sources showing research consumers how to understand and critically assess the statistical information and research results contained in technical research reports. In this respect, the review written by Mirko Savić in Panoeconomicus (2008, 2, pp. 249-252 will help the readers to get a more detailed overview of each chapters. I cordially urge the beginning researchers to pick a highlighter to conduct a detailed reading with the book. A thorough reading of the source will make the researchers quite selective in appreciating the harmony between the data analysis, results and discussion sections of typical journal articles. If interested, beginning researchers might begin with this book to grasp the basics of research statistics, and prop up their critical research reading skills with some statistics package applications through the help of Dr. Andy Field’s book, Discovering Statistics using SPSS (second edition published by Sage in 2005.
STATISTICAL METHODS IN HISTORY
Directory of Open Access Journals (Sweden)
Orlov A. I.
2016-01-01
Full Text Available We have given a critical analysis of statistical models and methods for processing text information in historical records to establish the times when there were certain events, ie, to build science-based chronology. There are three main kinds of sources of knowledge of ancient history: ancient texts, the remains of material culture and traditions. The specific date of the extracted by archaeologists objects in most cases can not be found. The group of Academician A.T. Fomenko has developed and applied new statistical methods for analysis of historical texts (Chronicle, based on the intensive use of computer technology. Two major scientific results were: the majority of historical records that we know now, are duplicated (in particular, chronicles, describing the so-called "Ancient Rome" and "Middle Ages", talking about the same events; the known historical chronicles tell us about real events, separated from the present time for not more than 1000 years. It was found that chronicles describing the history of "ancient times" and "Middle Ages" and the chronicle of Chinese history and the history of various European countries do not talk about different, but about the same events. We have the attempt of a new dating of historical events and restoring the true history of human society based on new data. From the standpoint of statistical methods of historical records and images of their fragments – they are special cases of non-numeric objects of nature. Therefore, developed by the group of A.T. Fomenko computer-statistical methods are the part of non-numerical statistics. We have considered some methods of statistical analysis of chronicles applied by the group of A.T. Fomenko: correlation method of maximums; dynasties method; the method of attenuation frequency; questionnaire method codes. New chronology allows us to understand much of the battle of ideas in modern science and mass consciousness. It becomes clear the root cause of cautious
Elementary statistical physics
Kittel, Charles
2004-01-01
Noteworthy for the philosophical subtlety of its foundations and the elegance of its problem-solving methods, statistical mechanics can be employed in a broad range of applications - among them, astrophysics, biology, chemistry, nuclear and solid state physics, communications engineering, metallurgy, and mathematics. Geared toward graduate students in physics, this text covers such important topics as stochastic processes and transport theory in order to provide students with a working knowledge of statistical mechanics.To explain the fundamentals of his subject, the author uses the method of
Introductory statistical thermodynamics
Dalarsson, Nils; Golubovic, Leonardo
2011-01-01
Introductory Statistical Thermodynamics is a text for an introductory one-semester course in statistical thermodynamics for upper-level undergraduate and graduate students in physics and engineering. The book offers a high level of detail in derivations of all equations and results. This information is necessary for students to grasp difficult concepts in physics that are needed to move on to higher level courses. The text is elementary, self contained, and mathematically well-founded, containing a number of problems with detailed solutions to help students to grasp the more difficult
Bayesian statistics an introduction
Lee, Peter M
2012-01-01
Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques. This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as wel
Milewski, Emil G
2012-01-01
REA's Essentials provide quick and easy access to critical information in a variety of different fields, ranging from the most basic to the most advanced. As its name implies, these concise, comprehensive study guides summarize the essentials of the field covered. Essentials are helpful when preparing for exams, doing homework and will remain a lasting reference source for students, teachers, and professionals. Statistics II discusses sampling theory, statistical inference, independent and dependent variables, correlation theory, experimental design, count data, chi-square test, and time se
Statistical Images Segmentation
Directory of Open Access Journals (Sweden)
Corina Curilă
2008-05-01
Full Text Available This paper deals with fuzzy statistical imagesegmentation. We introduce a new hierarchicalMarkovian fuzzy hidden field model, which extends to thefuzzy case the classical Pérez and Heitz hard model. Twofuzzy statistical segmentation methods related with themodel proposed are defined in this paper and we show viasimulations that they are competitive with, in some casesthan, the classical Maximum Posterior Mode (MPMbased methods. Furthermore, they are faster, which willshould facilitate extensions to more than two hard classesin future work. In addition, the model proposed isapplicable to the multiscale segmentation andmultiresolution images fusion problems.
Nonparametric statistical methods
Hollander, Myles; Chicken, Eric
2013-01-01
Praise for the Second Edition"This book should be an essential part of the personal library of every practicing statistician."-Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given sit
Computational statistical mechanics
Hoover, WG
1991-01-01
Computational Statistical Mechanics describes the use of fast computers to simulate the equilibrium and nonequilibrium properties of gases, liquids, and solids at, and away from equilibrium. The underlying theory is developed from basic principles and illustrated by applying it to the simplest possible examples. Thermodynamics, based on the ideal gas thermometer, is related to Gibb's statistical mechanics through the use of Nosé-Hoover heat reservoirs. These reservoirs use integral feedback to control temperature. The same approach is carried through to the simulation and anal
Statistics As Principled Argument
Abelson, Robert P
2012-01-01
In this illuminating volume, Robert P. Abelson delves into the too-often dismissed problems of interpreting quantitative data and then presenting them in the context of a coherent story about one's research. Unlike too many books on statistics, this is a remarkably engaging read, filled with fascinating real-life (and real-research) examples rather than with recipes for analysis. It will be of true interest and lasting value to beginning graduate students and seasoned researchers alike. The focus of the book is that the purpose of statistics is to organize a useful argument from quantitative
Neave, Henry R
2012-01-01
This book, designed for students taking a basic introductory course in statistical analysis, is far more than just a book of tables. Each table is accompanied by a careful but concise explanation and useful worked examples. Requiring little mathematical background, Elementary Statistics Tables is thus not just a reference book but a positive and user-friendly teaching and learning aid. The new edition contains a new and comprehensive "teach-yourself" section on a simple but powerful approach, now well-known in parts of industry but less so in academia, to analysing and interpreting process dat
Waller, Derek L
2008-01-01
Statistical analysis is essential to business decision-making and management, but the underlying theory of data collection, organization and analysis is one of the most challenging topics for business students and practitioners. This user-friendly text and CD-ROM package will help you to develop strong skills in presenting and interpreting statistical information in a business or management environment. Based entirely on using Microsoft Excel rather than more complicated applications, it includes a clear guide to using Excel with the key functions employed in the book, a glossary of terms and
Does Ignoring Multi-Destination Trips in the Travel Cost Method Cause a Systematic Downward Bias?
Kuosmanen, T.K.; Nillesen, E.E.M.; Wesseler, J.H.H.
2003-01-01
In theory, treating the multi-destination trips (MDTs) as single-destination trips (SDT) does not necessarily lead to biased results, because negative effect of price increase may be offset by the shift of the estimated demand curve. However, in our empirical application of the TCM zonal model to the valuation of the economic benefits of the Bellenden Kerr National Park in Australia we find (statistically significant) evidence that ignoring the MDTs leads to a dramatic overestimation of the c...
Impact of high-frequency waves on the ocean altimeter range bias - art. no. C11006
D. Vandemark; Chapron, Bertrand; Elfouhaily, T; Campbell, J.
2005-01-01
[1] New aircraft observations are presented on the range determination error in satellite altimetry associated with ocean waves. Laser-based measurements of the cross correlation between the gravity wave slope and elevation are reported for the first time. These observations provide direct access to a long, O(10 m), gravity wave statistic central to nonlinear wave theory prediction of the altimeter sea state bias. Coincident Ka-band radar scattering data are used to estimate an electromagneti...
Rudnick, Paul A.; WANG,Xia; Yan, Xinjian; Sedransk, Nell; Stein, Stephen E.
2014-01-01
Normalization is an important step in the analysis of quantitative proteomics data. If this step is ignored, systematic biases can lead to incorrect assumptions about regulation. Most statistical procedures for normalizing proteomics data have been borrowed from genomics where their development has focused on the removal of so-called ‘batch effects.’ In general, a typical normalization step in proteomics works under the assumption that most peptides/proteins do not change; scaling is then use...
Self-Biased-SMA Drive PU Microgripper with Force Sensing in Visual Servo
Ren-Jung Chang; Chih-Cheng Shiu; Chih-Yi Cheng
2013-01-01
An innovative design of a polyurethane microgripper system with force sensor is developed for the measurement of gripping force in vision-based control. A microgripper mechanism integrated with a force sensing arm is fabricated by an excimer laser. The microgripper is actuated by a self-biased-SMA (Shape Memory Alloy) actuator. A computer-vision method through the ERES (Extended Regional Edge Statistics) algorithm is employed to track the motion of gripper. The position information of the gri...
The 12th man? Refereeing bias in English and German soccer
Buraimo, B.; D. Forrest(School of Physics and Astronomy, Kelvin Building, The University of Glasgow, Glasgow, UK); Simmons, R
2010-01-01
The paper investigates potential bias in awards of player disciplinary sanctions, in the form of cautions (yellow cards) and dismissals (red cards) by referees in the English Premier League and the German Bundesliga. Previous studies of behaviour of soccer referees have not adequately incorporated within-game information. Descriptive statistics from our samples clearly show that home teams receive fewer yellow and red cards than away teams. These differences may be wrongly interpreted as evid...
Strick, Madelijn; Stoeckart, Peter F; Dijksterhuis, Ap
2015-11-01
It is a common research finding that conscious thought helps people to avoid racial discrimination. These three experiments, however, illustrate that conscious thought may increase biased face memory, which leads to increased judgment bias (i.e., preferring White to Black individuals). In Experiments 1 and 2, university students formed impressions of Black and White housemate candidates. They judged the candidates either immediately (immediate decision condition), thought about their judgments for a few minutes (conscious thought condition), or performed an unrelated task for a few minutes (unconscious thought condition). Conscious thinkers and immediate decision-makers showed a stronger face memory bias than unconscious thinkers, and this mediated increased judgment bias, although not all results were significant. Experiment 3 used a new, different paradigm and showed that a Black male was remembered as darker after a period of conscious thought than after a period of unconscious thought. Implications for racial prejudice are discussed. PMID:26164254
Geographic bias related to geocoding in epidemiologic studies
Directory of Open Access Journals (Sweden)
Siadaty Mir
2005-11-01
Full Text Available Abstract Background This article describes geographic bias in GIS analyses with unrepresentative data owing to missing geocodes, using as an example a spatial analysis of prostate cancer incidence among whites and African Americans in Virginia, 1990–1999. Statistical tests for clustering were performed and such clusters mapped. The patterns of missing census tract identifiers for the cases were examined by generalized linear regression models. Results The county of residency for all cases was known, and 26,338 (74% of these cases were geocoded successfully to census tracts. Cluster maps showed patterns that appeared markedly different, depending upon whether one used all cases or those geocoded to the census tract. Multivariate regression analysis showed that, in the most rural counties (where the missing data were concentrated, the percent of a county's population over age 64 and with less than a high school education were both independently associated with a higher percent of missing geocodes. Conclusion We found statistically significant pattern differences resulting from spatially non-random differences in geocoding completeness across Virginia. Appropriate interpretation of maps, therefore, requires an understanding of this phenomenon, which we call "cartographic confounding."
Mooney, R J
1996-01-01
This paper describes an experimental comparison of seven different learning algorithms on the problem of learning to disambiguate the meaning of a word from context. The algorithms tested include statistical, neural-network, decision-tree, rule-based, and case-based classification techniques. The specific problem tested involves disambiguating six senses of the word ``line'' using the words in the current and proceeding sentence as context. The statistical and neural-network methods perform the best on this particular problem and we discuss a potential reason for this observed difference. We also discuss the role of bias in machine learning and its importance in explaining performance differences observed on specific problems.
Kingdon, Geeta Gandhi
2005-01-01
The reliability of the household consumption-based (Engel curve) methodology in detecting gender bias has been called into question because it has generally failed to confirm bias even where it exists. This article seeks to find explanations for this failure by exploiting a data set that has educational expenditure information at the individual level and also, by aggregation, at the household level. I find that, in the basic education age groups, the discriminatory mechanism in education is v...