This updated, bestselling book continues to be one of the only Bayesian statistics texts designed for social scientists. Incorporating new research and additional material, the third edition presents state-of-the-art guidance on Bayesian statistical computing. It emphasizes Markov chain Monte Carlo (MCMC) and computation with R and WinBUGS. Along with doubling the number of exercises, this edition covers time series, decision theory, nonparametric models, and mixture models. A solutions manual is available with qualifying course adoption.

Jeff Gill is a professor in the Department of Political Science, the Division of Biostatistics, and the Department of Surgery (Public Health Sciences) at Washington University. He is the author of several books and has published numerous research articles. His research applies Bayesian modeling and data analysis to questions in general social science quantitative methodology, political behavior and institutions, and medical/health data analysis using computationally intensive tools. He received his B.A. from UCLA, MBA from Georgetown University, Ph.D. from American University, and Post-Doctorate from Harvard University.