Doing Bayesian Data Analysis
by John K. Kruschke
- 7 Want to read
"There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis tractable and accessible to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS, is for first year graduate students or advanced undergraduates and provides an accessible approach, as all mathematics is explained intuitively and with concrete examples. It assumes only algebra and a rustya calculus. Unlike other textbooks, this book begins with the basics, including essential concepts of probability and random sampling. The book gradually climbs all the way to advanced hierarchical modeling methods for realistic data. The text provides complete examples with the R programming language and BUGS software (both freeware), and begins with basic programming examples, working up gradually to complete programs for complex analyses and presentation graphics. These templates can be easily adapted for a large variety of students and their own research needs.The textbook bridges the students from their undergraduate training into modern Bayesian methods." - Publisher's description.
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Previews available in: English
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Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan
2015, Academic Press
- Second Edition
0124058884 9780124058880
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Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan
2014, Elsevier Science & Technology Books
in English
0124059163 9780124059160
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Doing Bayesian Data Analysis: A Tutorial Introduction with R
2010, Elsevier Science & Technology Books
in English
0123814863 9780123814869
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Work Description
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 step-by-step 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 high-level 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 metric-predicted variable on one or two groups; metric-predicted variable with one metric predictor; metric-predicted variable with multiple metric predictors; metric-predicted variable with one nominal predictor; and metric-predicted variable with multiple nominal predictors. The exercises found in the text have explicit purposes and guidelines for accomplishment.
This book is intended for first-year 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 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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- Created January 25, 2013
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| April 29, 2025 | Edited by MARC Bot | import existing book |
| December 13, 2022 | Edited by MARC Bot | import existing book |
| November 13, 2020 | Edited by MARC Bot | import existing book |
| October 9, 2020 | Edited by ImportBot | import existing book |
| January 25, 2013 | Created by Sunil Kim | Added new book. |