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Doing Bayesian Data Analysis

A Tutorial with R, JAGS, and Stan

Autor: John Kruschke

Język:

Oprawa: Twarda

Wydawca: Elsevier Science Publishing Co Inc

Dostępność: Dostępna u dostawcy w małych ilościach

Wysyłamy za 13-18 dni

397.37 zł

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

Informacje o książce

Autor

John Kruschke

Język

Angielski

Oprawa

Książka - Twarda

Data wydania

2014

strony

776

EAN

9780124058880

ISBN

0124058884

Enbook ID

02784969

Wydawca

Elsevier Science Publishing Co Inc

Waga

1960

Wymiary

236 x 199 x 38

Pełny opis

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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A Tutorial with R, JAGS, and Stan

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