Description

• Fundamentals of Bayesian inference in single and multi-parameter models for inference and decision making, including simulation of posterior distributions, Markov chain Monte Carlo methods, hierarchical models, and empirical Bayes models.

Prequisites

• Graduate standing, and Statistics and Data Sciences 382, Mathematics 362K and 378K, or consent of instructor.