Doing Bayesian Data Analysis: A Tutorial with R and BUGS
Author: John Kruschke
Publisher: Academic Press
Call Number: QA279.5 .K79 2011
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 Introduction with R and BUGS 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, multiple regression, and chi-square (contingency table analysis).
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. Prerequisite is knowledge of algebra and basic calculus.
John K. Kruschke has taught Bayesian data analysis, mathematical modeling, and traditional statistical methods for over 20 years. He is five-time winner of Teaching Excellence Recognition Awards from Indiana University, where he is Professor of Psychological and Brain Sciences, and Adjunct Professor of Statistics. He has also presented numerous tutorials, workshops, or symposia on Bayesian data analysis (see this partial list). His research interests include the science or morality, applications of Bayesian methods to adaptive teaching and learning, and models of attention in learning, which he has developed in both connectionist and Bayesian formalisms. He received a Troland Research Award from the National Academy of Sciences. He is an Action Editor for the Journal of Mathematical Psychology, and he is or has been on the editorial boards of several journals, including Psychological Review, the Journal of Experimental Psychology: General, and Psychonomic Bulletin & Review.
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