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Doing Bayesian Data Analysis: A Tutorial with R and BUGS John K. Kruschke
Publisher: Academic Press

Bolstad; Doing Bayesian Data Analysis: A Tutorial with R and BUGS, John K. Doing Bayesian Data Analysis – A Tutorial with R and BUGS by John K. Genuinely accessible to beginners: • An entire chapter on Bayes' rule, with intuitive examples and emphasis on application to data and models. All three books use R and BUGS, the standard software for Bayesian work. As a starting point, I'd add Doing Bayesian Data Analysis by John Kruschke and Bayesian Computation with R by Jim Albert to the list . (This article was originally published at Doing Bayesian Data Analysis, and syndicated at StatsBlogs.) In a thread elsewhere, a reader of In this post I briefly review Abelson's paradox and demonstrate how hierarchical Bayesian data analysis is actually applied to real baseball data of the type that Abelson used to illustrate his paradox. His well commented R-Code can get you into some simple roll-your-own MCMC and Gibbs sampling and his tutorial-like handling of WinBUGS in the raw and through R2WinBUGS is, I think, the best. Doing Bayesian Data Analysis: A Tutorial with R and BUGS 9780123814852 Kruschke ** Brand New **. Probability Theory: The Logic of Science, E. Jaynes; Introduction to Bayesian statistics, William M.