Doing Bayesian Data Analysis
A Tutorial with R, JAGS, and Stan

Buch (gebundene Ausgabe, Englisch)

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Beschreibung
Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples. Included are stepbystep instructions on how to carry out Bayesian data analyses in the popular and free software R and WinBugs, as well as new programs in JAGS and Stan. The new programs are designed to be much easier to use than the scripts in the first edition. In particular, there are now compact highlevel scripts that make it easy to run the programs on your own data sets.
The book is divided into three parts and begins with the basics: models, probability, Bayes' rule, and the R programming language. The discussion then moves to the fundamentals applied to inferring a binomial probability, before concluding with chapters on the generalized linear model. Topics include metricpredicted variable on one or two groups; metricpredicted variable with one metric predictor; metricpredicted variable with multiple metric predictors; metricpredicted variable with one nominal predictor; and metricpredicted variable with multiple nominal predictors. The exercises found in the text have explicit purposes and guidelines for accomplishment.
This book is intended for firstyear graduate students or advanced undergraduates in statistics, data analysis, psychology, cognitive science, social sciences, clinical sciences, and consumer sciences in business.
Accessible, including the basics of essential concepts of probability and random sampling
Examples with R programming language and JAGS software
Comprehensive coverage of all scenarios addressed by nonBayesian textbooks: ttests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chisquare (contingency table analysis)
Coverage of experiment planning
R and JAGS computer programming code on website
Exercises have explicit purposes and guidelines for accomplishment
Provides stepbystep instructions on how to conduct Bayesian data analyses in the popular and free software R and WinBugs
"Both textbook and practical guide, this work is an accessible account of Bayesian data analysis starting from the basics.This edition is truly an expanded work and includes all new programs in JAGS and Stan designed to be easier to use than the scripts of the first edition, including when running the programs on your own data sets."  MAA Reviews
"fills a gaping hole in what is currently available, and will serve to create its own market" Prof. Michael Lee, U. of Cal., Irvine; pres. Society for Mathematical Psych
"has the potential to change the way most cognitive scientists and experimental psychologists approach the planning and analysis of their experiments" Prof. Geoffrey Iverson, U. of Cal., Irvine; past pres. Society for Mathematical Psych.
"better than others for reasons stylistic.... buy it  it's truly amazin'!" James L. (Jay) McClelland, Lucie Stern Prof. & Chair, Dept. of Psych., Stanford U.
"the best introductory textbook on Bayesian MCMC techniques" J. of Mathematical Psych.
"potential to change the methodological toolbox of a new generation of social scientists" J. of Economic Psych.
"revolutionary" British J. of Mathematical and Statistical Psych.
"writing for real people with real data. From the very first chapter, the engaging writing style will get readers excited about this topic" PsycCritiques
Kruschke, John
John K. Kruschke is Professor of Psychological and Brain Sciences, and Adjunct Professor of Statistics, at Indiana University in Bloomington, Indiana, USA. He is eighttime winner of Teaching Excellence Recognition Awards from Indiana University. He won the Troland Research Award from the National Academy of Sciences (USA), and the Remak Distinguished Scholar Award from Indiana University. He has been on the editorial boards of various scientific journals, including Psychological Review, the Journal of Experimental Psychology: General, and the Journal of Mathematical Psychology, among others.
After attending the Summer Science Program as a high school student and considering a career in astronomy, Kruschke earned a bachelor's degree in mathematics (with high distinction in general scholarship) from the University of California at Berkeley. As an undergraduate, Kruschke taught selfdesigned tutoring sessions for many math courses at the Student Learning Center. During graduate school he attended the 1988 Connectionist Models Summer School, and earned a doctorate in psychology also from U.C. Berkeley. He joined the faculty of Indiana University in 1989. Professor Kruschke's publications can be found at his Google Scholar page. His current research interests focus on moral psychology.
Professor Kruschke taught traditional statistical methods for many years until reaching a point, circa 2003, when he could no longer teach corrections for multiple comparisons with a clear conscience. The perils of p values provoked him to find a better way, and after only several thousand hours of relentless effort, the 1st and 2nd editions of Doing Bayesian Data Analysis emerged.
Produktdetails
Einband  gebundene Ausgabe 

Seitenzahl  776 
Erscheinungsdatum  01.01.2015 
Sprache  Englisch 
ISBN  9780124058880 
Reihe  Academic Press 
Verlag  Elsevier LTD, Oxford 

Maße (L/B/H)  24.1/19.5/4.5 cm 
Gewicht  1762 g 
Abbildungen  Approx. 175 illustrations 
Auflage  2nd revised edition 