BAYESIAN DATA ANALYSIS (2 SCU)

Learning Outcomes:

On successful completion of this course, students will be able to: explain the principles and techniques of Bayesian data analysis; apply Bayesian methodology to solve real-life problems; interpret Bayesian computation, visualization, and analysis of data.

Topics:

1. Introduction to Bayesian Inference;
2. Single Parameter Models;
3. Hierarchical models;
4. Model checking;
5. Introduction to Bayesian computation;
6. Basics of Markov chain simulation;
7. Application of MCMC.