Principles of Bayesian estimation, testing and prediction; Bayes factors and posterior probabilities of hypotheses; hierarchical modeling; Bayesian model selection and assessment; Bayesian computation and asymptotics; nonparametric Bayesian models.
Requisites: Prerequisite: STAT 713 and STAT 771, plus one introductory course in statistical computing (e.g. STAT 725 or STAT 726 or equivalent background).