Doing Bayesian Data Analysis

A Tutorial with R, JAGS, and Stan

Автор: John Kruschke

Език:

Корици: С твърди корици

Издател: Elsevier Science Publishing Co Inc

Наличност: Външен склад в ограничено количество

Изпращаме след 13-18 дни

97.90 € 191.47 лв

There is an explosion of interest in Bayesian statistics, primarily because recently created computa...

Информация за книгата

Автор

John Kruschke

Език

Английски език

Корици

Книга - С твърди корици

Издадена

2014

страници

776

EAN

9780124058880

ISBN

0124058884

Enbook ID

02784969

Издател

Elsevier Science Publishing Co Inc

Теглоt

1960

Размери

236 x 199 x 38

Пълно описание

There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis obtainable to a wide audience. Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan provides an accessible approach to Bayesian data analysis, as material is explained clearly with concrete examples. The book begins with the basics, including essential concepts of probability and random sampling, and gradually progresses to advanced hierarchical modeling methods for realistic data. The text delivers comprehensive coverage of all scenarios addressed by non-Bayesian textbooks: t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, correlation, multiple regression, and chi-square (contingency table analysis). Included are step-by-step instructions on how to conduct Bayesian data analyses in the popular and free software R and WinBugs. This book is intended for first-year graduate students or advanced undergraduates. It provides a bridge between undergraduate training and modern Bayesian methods for data analysis, which is becoming the accepted research standard. Knowledge of algebra and basic calculus is a prerequisite. * 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 non-Bayesian textbooks: t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis)* Coverage of experiment planning* R and JAGS computer programming code on website* Exercises have explicit purposes and guidelines for accomplishment* Provides step-by-step instructions on how to conduct Bayesian data analyses in the popular and free software R and WinBugs.

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Doing Bayesian Data Analysis

A Tutorial with R, JAGS, and Stan

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