Doing Bayesian Data Analysis: A Tutorial With R and Bugs
Language: English
Published by Academic Press, 2011
- Hardcover
- Used
Seller: Anybook.com, Lincoln, United KingdomAnybook.com
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This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In fair condition, suitable as a study copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1400grams, ISBN:9780123814852.
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- Title
- Doing Bayesian Data Analysis: A Tutorial With R and Bugs
- Author
- John K. Kruschke
- Publisher
- Academic Press
- Publication year
- 2011
- Condition
- Fair
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0123814855
- ISBN 13
- 9780123814852
- Item weight
- 1,400 grams
- Seller catalogs
- Mathematics
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 ‘rusty’ 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.
- Accessible, including the basics of essential concepts of probability and random sampling
- Examples with R programming language and BUGS 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 BUGS computer programming code on website
- Exercises have explicit purposes and guidelines for accomplishment
"Synopsis" may belong to another edition of this title.
About the Author
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 self-designed 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.
"About the title" may belong to another edition of this title.
Anybook.com
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AbeBooks seller since December 22, 1999
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