Applied Bayesian Modeling and Inference; PBHS 43010
Course Instructor: Yuan Ji
PQ: STAT 24400 and STAT 24500 or master level training in statistics.
ID: STAT 35920
Course begins with basic probability and distribution theory, and covers a wide range of topics related to Bayesian modeling, computation, and inference. Significant amount of effort will be directed to teaching students on how to build and apply hierarchical
models and perform posterior inference. The first half of the course will be focused on basic theory, modeling, and computation using Markov chain Monte Carlo methods, and the second half of the course will be about advanced models and applications. Computation
and application will be emphasized so that students will be able to solve real-world problems with Bayesian techniques.