Probability basics for Bayesian statistics. Bayesian inference for simple exponential families. Markov Chain Monte Carlo for posterior inference. Empirical Bayes. Hierarchical Bayes. Bayesian inference for the multivariate normal model. Bayesian linear regression. More advanced topics may be included. Computer software will be used. Includes: Experiential Learning Activity Prerequisite(s): STAT 3553 or permission of the School. Lectures three hours a week, laboratory one hour a week. [0.5 credits]
Probability basics for Bayesian statistics. Bayesian inference for simple exponential families. Markov Chain Monte Carlo for posterior inference. Empirical Bayes. Hierarchical Bayes. Bayesian inference for the multivariate normal model. Bayesian linear regression. More advanced topics may be included. Computer software will be used. Includes: Experiential Learning Activity Prerequisite(s): STAT 3553 or permission of the School. Lectures three hours a week, laboratory one hour a week. [0.5 credits]
