SRM 636 Applied Bayesian Statistics
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
Prerequisite
SRM 502 with a minimum grade of C