Doing Bayesian Data Analysis - Info and Reading Options
By John K. Kruschke

"Doing Bayesian Data Analysis" was published by Academic Press in 2010, it has 653 pages and the language of the book is English.
“Doing Bayesian Data Analysis” Metadata:
- Title: Doing Bayesian Data Analysis
- Author: John K. Kruschke
- Language: English
- Number of Pages: 653
- Publisher: Academic Press
- Publish Date: 2010
“Doing Bayesian Data Analysis” Subjects and Themes:
- Subjects: ➤ Bayesian statistical decision theory - R (Computer program language) - Programming languages (electronic computers) - Bayes-Verfahren - R. - General - Mathematics & statistics -> mathematics -> mathematics general - Mathematics & statistics -> mathematics -> probability - r
Edition Identifiers:
- The Open Library ID: OL25421769M - OL16799762W
- Online Computer Library Center (OCLC) ID: 653121532
- Library of Congress Control Number (LCCN): 2010030206
- ISBN-13: 9780123814852
- All ISBNs: 9780123814852
AI-generated Review of “Doing Bayesian Data Analysis”:
"Doing Bayesian Data Analysis" Description:
The Open Library:
"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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