Bayesian Statistics

Catalog description

Bayesian Statistics (3) This course covers principles and applications of modern Bayesian statistical analysis, with a focus on the type of data analysis work done by social, biomedical scientists, and others. This includes inference, prediction, and the presentation of Bayesian model outcomes through hypothesis tests, interval analysis, quantile summaries, and graphical analysis. Since modern Bayesian analysis relies heavily on computational tools, the course includes a strong emphasis on Markov chain Monte Carlo and related techniques in order to produce results that are not otherwise available. Other topics include hierarchical Bayesian specifications and Bayesian nonparametrics. Crosslist: STAT-618. Grading: A-F only. Prerequisite: STAT-614.