“The second edition was reviewed in JASA by Maiti (2004) ? we now stand 10 years later with an even more impressive textbook that truly stands for what Bayesian data analysis should be. ? this being a third edition begets the question of what is new when compared with the second edition? Quite a lot ? this is truly the reference book for a graduate course on Bayesian statistics and not only Bayesian data analysis.”
?Christian P. Robert, Journal of the American Statistical Association, September 2014, Vol. 109

Praise for the Second Edition
? it is simply the best all-around modern book focused on data analysis currently available. ? There is enough important additional material here that those with the first edition should seriously consider updating to the new version. ? when students or colleagues ask me which book they need to start with in order to take them as far as possible down the road toward analyzing their own data, Gelman et al. has been my answer since 1995. The second edition makes this an even more robust choice.
?Lawrence Joseph, Montreal General Hospital and McGill University, Statistics in Medicine, Vol. 23, 2004

I am thoroughly excited to have this book in hand to supplement course material and to offer research collaborators and clients at our consulting lab more sophisticated methods to solve their research problems.
?John Grego, University of South Carolina, USA

? easily the most comprehensive, scholarly, and thoughtful book on the subject, and I think will do much to promote the use of Bayesian methods
?David Blackwell, University of California, Berkeley, USA

Andrew Gelman is Professor of Statistics and Professor of Political Science at Columbia University. He has published over 150 articles in statistical theory, methods, and computation, and in applications areas including decision analysis, survey sampling, political science, public health, and policy. His other books are Bayesian Data Analysis (1995, second edition 2003) and Teaching Statistics: A Bag of Tricks (2002).

Donald B. Rubin is John L. Loeb Professor of Statistics at Harvard University, where he has been professor since 1983 and department chair for thirteen of those years. He has authored or coauthored nearly four hundred publications (including ten books), has four joint patents, and has made important contributions to statistical theory and methodology, particularly in causal inference, design and analysis of experiments and sample surveys, treatment of missing data, and Bayesian data analysis. Rubin has received the Samuel S. Wilks Medal from the American Statistical Association, the Parzen Prize for Statistical Innovation, the Fisher Lectureship, and the George W. Snedecor Award from the Committee of Presidents of Statistical Societies. He was named Statistician of the Year by the American Statistical Association, Boston and Chicago chapters. He is one of the most highly cited authors in mathematics and economics with nearly 150,000 citations to date. –This text refers to an alternate kindle_edition edition.