SRM 636 Applied Bayesian Statistics

Prerequisites: SRM 502 and consent of instructor. This course provides an introduction to Bayesian statistical methods for inference. Topics include prior, likelihood, posterior, and predictive distributions, Bayesian analysis of single parameter models and simple multi-parameter models using conjugate, non-informative and informative priors, hierarchical modeling, and simulation of posterior distributions and posterior summaries using statistical packages.

Credits

3