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Relative Distribution Methods In The Social Sciences

Author: Mark S. Handcock
Publisher: Springer Science & Business Media
ISBN: 0387226583
Size: 69.69 MB
Format: PDF, Kindle
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This monograph presents methods for full comparative distributional analysis based on the relative distribution. This provides a general integrated framework for analysis, a graphical component that simplifies exploratory data analysis and display, a statistically valid basis for the development of hypothesis-driven summary measures, and the potential for decomposition - enabling the examination of complex hypotheses regarding the origins of distributional changes within and between groups. Written for data analysts and those interested in measurement, the text can also serve as a textbook for a course on distributional methods.

Modern Statistics For The Social And Behavioral Sciences

Author: Rand Wilcox
Publisher: CRC Press
ISBN: 1439834563
Size: 12.39 MB
Format: PDF, Mobi
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In addition to learning how to apply classic statistical methods, students need to understand when these methods perform well, and when and why they can be highly unsatisfactory. Modern Statistics for the Social and Behavioral Sciences illustrates how to use R to apply both standard and modern methods to correct known problems with classic techniques. Numerous illustrations provide a conceptual basis for understanding why practical problems with classic methods were missed for so many years, and why modern techniques have practical value. Designed for a two-semester, introductory course for graduate students in the social sciences, this text introduces three major advances in the field: Early studies seemed to suggest that normality can be assumed with relatively small sample sizes due to the central limit theorem. However, crucial issues were missed. Vastly improved methods are now available for dealing with non-normality. The impact of outliers and heavy-tailed distributions on power and our ability to obtain an accurate assessment of how groups differ and variables are related is a practical concern when using standard techniques, regardless of how large the sample size might be. Methods for dealing with this insight are described. The deleterious effects of heteroscedasticity on conventional ANOVA and regression methods are much more serious than once thought. Effective techniques for dealing heteroscedasticity are described and illustrated. Requiring no prior training in statistics, Modern Statistics for the Social and Behavioral Sciences provides a graduate-level introduction to basic, routinely used statistical techniques relevant to the social and behavioral sciences. It describes and illustrates methods developed during the last half century that deal with known problems associated with classic techniques. Espousing the view that no single method is always best, it imparts a general understanding of the relative merits of various techniques so that the choice of method can be made in an informed manner.

Statistical Inference

Author: Michael W. Oakes
Publisher: John Wiley & Sons
ISBN: 9780471104438
Size: 72.52 MB
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Critical analysis of the use of statistical inference in social and behavioural research, its proper role, logic, and its abuse. Argues that ignorance and misunderstanding of the role of statistical inference has had a detrimental effect upon research in the field. Points the way to an appropriate appreciation of the part played by quantification in these disciplines. Examines the significance test versus interval estimation and evaluates Neyman-Pearson, Fisherian, Bayesian, and Likelihood inference. Presents arguments in a plainly written, easily understood manner.

Essentials Of Statistics For The Social And Behavioral Sciences

Author: Barry H. Cohen
Publisher: John Wiley & Sons
ISBN: 0471480762
Size: 45.82 MB
Format: PDF, Mobi
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Master the essential statistical skills used in social and behavioral sciences Essentials of Statistics for the Social and Behavioral Sciences distills the overwhelming amount of material covered in introductory statistics courses into a handy, practical resource for students and professionals. This accessible guide covers basic to advanced concepts in a clear, concrete, and readable style. Essentials of Statistics for the Social and Behavioral Sciences guides you to a better understanding of basic concepts of statistical methods. Numerous practical tips are presented for selecting appropriate statistical procedures. In addition, this useful guide demonstrates how to evaluate and interpret statistical data, provides numerous formulas for calculating statistics from tables of summary statistics, and offers a variety of worked examples. As part of the Essentials of Behavioral Science series, this book offers a thorough review of the most relevant statistical concepts and techniques that will arm you with the tools you'll need for knowledgeable, informed practice. Each concise chapter features numerous callout boxes highlighting key concepts, bulleted points, and extensive illustrative material, as well as "Test Yourself" questions that help you gauge and reinforce your grasp of the information covered.

Assessing Inequality

Author: Lingxin Hao
Publisher: SAGE Publications
ISBN: 1483342638
Size: 15.20 MB
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Providing basic foundations for measuring inequality from the perspective of distributional properties This monograpg reviews a set of widely used summary inequality measures, and the lesser known relative distribution method provides the basic rationale behind each measure and discusses their interconnections. It also introduces model-based decomposition of inequality over time using quantile regression. This approach enables researchers to estimate two different contributions to changes in inequality between two time points. Key Features Clear statistical explanations provide fundamental statistical basis for understanding the new modeling framework Straightforward empirical examples reinforce statistical knowledge and ready-to-use procedures Multiple approaches to assessing inequality are introduced by starting with the basic distributional property and providing connections among approaches This supplementary text is appropriate for any graduate-level, intermediate, or advanced statistics course across the social and behavioral sciences, as well as individual researchers. Learn more about "The Little Green Book" - QASS Series! Click Here

Statistical Methods For The Social And Behavioural Sciences

Author: David B. Flora
Publisher: SAGE
ISBN: 1526421925
Size: 78.97 MB
Format: PDF
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Statistical methods in modern research increasingly entail developing, estimating and testing models for data. Rather than rigid methods of data analysis, the need today is for more flexible methods for modelling data. In this logical, easy-to-follow and exceptionally clear book, David Flora provides a comprehensive survey of the major statistical procedures currently used. His innovative model-based approach teaches you how to: Understand and choose the right statistical model to fit your data Match substantive theory and statistical models Apply statistical procedures hands-on, with example data analyses Develop and use graphs to understand data and fit models to data Work with statistical modeling principles using any software package Learn by applying, with input and output files for R, SAS, SPSS, and Mplus. Statistical Methods for the Social and Behavioural Sciences: A Model Based Approach is the essential guide for those looking to extend their understanding of the principles of statistics, and begin using the right statistical modeling method for their own data. It is particularly suited to second or advanced courses in statistical methods across the social and behavioural sciences.

Statistical Power Analysis For The Behavioral Sciences

Author: Jacob Cohen
Publisher: Routledge
ISBN: 1134742770
Size: 69.46 MB
Format: PDF, ePub
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Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.

Multidimensional Item Response Theory

Author: M.D. Reckase
Publisher: Springer Science & Business Media
ISBN: 9780387899763
Size: 66.13 MB
Format: PDF, ePub, Docs
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First thorough treatment of multidimensional item response theory Description of methods is supported by numerous practical examples Describes procedures for multidimensional computerized adaptive testing

Introduction To Applied Bayesian Statistics And Estimation For Social Scientists

Author: Scott M. Lynch
Publisher: Springer Science & Business Media
ISBN: 0387712658
Size: 21.98 MB
Format: PDF, Mobi
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This book outlines Bayesian statistical analysis in great detail, from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models that are most commonly used in social science research - including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data example in painstaking detail.

Statistical Methods For The Social And Behavioural Sciences

Author: David B. Flora
Publisher: SAGE
ISBN: 1526421925
Size: 13.25 MB
Format: PDF, Mobi
View: 4624
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Statistical methods in modern research increasingly entail developing, estimating and testing models for data. Rather than rigid methods of data analysis, the need today is for more flexible methods for modelling data. In this logical, easy-to-follow and exceptionally clear book, David Flora provides a comprehensive survey of the major statistical procedures currently used. His innovative model-based approach teaches you how to: Understand and choose the right statistical model to fit your data Match substantive theory and statistical models Apply statistical procedures hands-on, with example data analyses Develop and use graphs to understand data and fit models to data Work with statistical modeling principles using any software package Learn by applying, with input and output files for R, SAS, SPSS, and Mplus. Statistical Methods for the Social and Behavioural Sciences: A Model Based Approach is the essential guide for those looking to extend their understanding of the principles of statistics, and begin using the right statistical modeling method for their own data. It is particularly suited to second or advanced courses in statistical methods across the social and behavioural sciences.