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Bayesian Statistics for the Social Sciences (Methodology in the Social Sciences) (Englisch) Gebundene Ausgabe – 23. Juli 2014

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Produktbeschreibungen

Pressestimmen

"We are all Bayesians at heart--in that we all have prior knowledge--so why use a frequentist approach to statistics? This book can help you understand and implement a Bayesian approach."--John J. McArdle, PhD, Department of Psychology, University of Southern California

"This much-needed book bridges the gap between Bayesian statistics and social sciences. It provides the reader with basic knowledge and practical skills for applying Bayesian methodologies to data-analysis problems. The focus on Bayesian psychometric modeling is noteworthy and unique."--Jay Myung, PhD, Department of Psychology, Ohio State University

"Bayesian analysis has arrived--and Kaplan has written exactly the book that social science faculty members and graduate students need in order to learn Bayesian statistics. It is sophisticated yet accessible, complete yet an easy read. This book will ride the crest of the Bayesian wave for years to come."--William R. Shadish, PhD, Department of Psychological Sciences, University of California, Merced

"I like that this book is concise but very comprehensive, with topics ranging from the basic regression model to the advanced mixture model. Well-organized sections move from foundations; to model building, basic regression, and generalized linear models; to advanced topics. The author's explanations of concepts and examples are clear and straightforward. He has chosen his examples well; they address very commonly studied research questions in the educational sciences. The ability to access the code and data online will benefit researchers and students tremendously."--Feifei Ye, PhD, Department of Psychology in Education, University of Pittsburgh




-Bayesian analysis has arrived--and Kaplan has written exactly the book that social science faculty members and graduate students need in order to learn Bayesian statistics. It is sophisticated yet accessible, complete yet an easy read. This book will ride the crest of the Bayesian wave for years to come.---William R. Shadish, PhD, Department of Psychological Sciences, University of California, Merced

-I like that this book is concise but very comprehensive, with topics ranging from the basic regression model to the advanced mixture model. Well-organized sections move from foundations; to model building, basic regression, and generalized linear models; to advanced topics. The author's explanations of concepts and examples are clear and straightforward. He has chosen his examples well; they address very commonly studied research questions in the educational sciences. The ability to access the code and data online will benefit researchers and students tremendously.---Feifei Ye, PhD, Department of Psychology in Education, University of Pittsburgh

-We are all Bayesians at heart--in that we all have prior knowledge--so why use a frequentist approach to statistics? This book can help you understand and implement a Bayesian approach.---John J. McArdle, PhD, Department of Psychology, University of Southern California

-This much-needed book bridges the gap between Bayesian statistics and social sciences. It provides the reader with basic knowledge and practical skills for applying Bayesian methodologies to data-analysis problems. The focus on Bayesian psychometric modeling is noteworthy and unique.---Jay Myung, PhD, Department of Psychology, Ohio State University






"Bayesian analysis has arrived--and Kaplan has written exactly the book that social science faculty members and graduate students need in order to learn Bayesian statistics. It is sophisticated yet accessible, complete yet an easy read. This book will ride the crest of the Bayesian wave for years to come."--William R. Shadish, PhD, Department of Psychological Sciences, University of California, Merced

"I like that this book is concise but very comprehensive, with topics ranging from the basic regression model to the advanced mixture model. Well-organized sections move from foundations; to model building, basic regression, and generalized linear models; to advanced topics. The author's explanations of concepts and examples are clear and straightforward. He has chosen his examples well; they address very commonly studied research questions in the educational sciences. The ability to access the code and data online will benefit researchers and students tremendously."--Feifei Ye, PhD, Department of Psychology in Education, University of Pittsburgh

"We are all Bayesians at heart--in that we all have prior knowledge--so why use a frequentist approach to statistics? This book can help you understand and implement a Bayesian approach."--John J. McArdle, PhD, Department of Psychology, University of Southern California

"This much-needed book bridges the gap between Bayesian statistics and social sciences. It provides the reader with basic knowledge and practical skills for applying Bayesian methodologies to data-analysis problems. The focus on Bayesian psychometric modeling is noteworthy and unique."--Jay Myung, PhD, Department of Psychology, Ohio State University




Über den Autor und weitere Mitwirkende

David Kaplan, PhD, is Professor of Quantitative Methods in the Department of Educational Psychology at the University of Wisconsin-Madison and holds affiliate appointments in the Department of Population Health Sciences and the Center for Demography and Ecology. Dr. Kaplan's program of research focuses on the development of Bayesian statistical methods for education research. His work on these topics is directed toward application to quasi-experimental and large-scale cross-sectional and longitudinal survey designs. He is most actively involved in the Program for International Student Assessment, sponsored by the Organisation for Economic Co-operation and Development--he served on its Technical Advisory Group from 2005 to 2009 and currently serves as Chair of its Questionnaire Expert Group. Dr. Kaplan also is a member of the Questionnaire Standing Committee of the U.S. National Assessment of Educational Progress, is a Fellow of the American Psychological Association (Division 5), and was a Jeanne Griffith Fellow at the National Center for Education Statistics.


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am 9. November 2015
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Amazon.com: 4,2 von 5 Sternen 4 Rezensionen
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3,0 von 5 SternenGood conceptual exegesis with off-putting code sections
am 1. Dezember 2014 - Veröffentlicht auf Amazon.com
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3,0 von 5 SternenToo advanced for the beginners and too basic for the experts.
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5,0 von 5 SternenGreat for the frequentist-trained social science graduate student but I ...
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4,0 von 5 SternenSubpar as introduction, but much better in intermediate territory
am 19. November 2014 - Veröffentlicht auf Amazon.com
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