STAT8310 - Bayesian Data Analysis
Spring 2027
Preface
Spring 2027
Welcome to STAT 8310 - Bayesian Data Analysis. This course website is being prepared for Spring 2027. Course arrangements, assessment details, and the lecture schedule are tentative and will be updated before the semester begins.
Course materials: Full course notes (PDF) · GitHub repository (2027S) · Project guidelines.
Description
This course will cover the topics in the theory and practice of Bayesian statistical inference, ranging from a review of fundamentals to questions of current research interest. Motivation for the Bayesian approach. Bayesian computation, Monte Carlo methods, asymptotics. Model checking and comparison. A selection of examples and issues in modelling and data analysis. Discussion of advantages and difficulties of the Bayesian approach. This course will be computationally intensive through analysis of data sets using the R statistical computing language.
Prerequisites
MATH 4752/6752 – Mathematical Statistics II or equivalent, and the ability to program in a high-level language.
Instructor
Chi-Kuang Yeh, Assistant Professor in the Department of Mathematics and Statistics, Georgia State University.
- Office: Suite 1407, 25 Park Place.
- Email: cyeh@gsu.edu.
Office Hour
To be announced.
Grade Distribution (Tentative)
- Homework – 50%
- Exam – 30%
- Final – 20%
Assignments
Assignments and due dates will be announced.
Midterm
The midterm date will be announced.
Final Project
The final project deadline will be announced. See the project page for tentative guidelines.
Planned Topics
The following topics are tentative. The lecture schedule will be announced.
| Status | Chapter | Topic | Lecture |
|---|---|---|---|
| ⏳ | Ch. 1 | Welcome and Overview | TBA |
| ⏳ | Appendix A | Intro to R Programming | TBA |
| ⏳ | Ch. 2 | Probability and Exchangeability | TBA |
| ⏳ | Ch. 3 | One Parameter Models | TBA |
| ⏳ | Ch. 4 | Monte Carlo | TBA |
| ⏳ | Ch. 5 | Gibbs Sampler | TBA |
| ⏳ | Appendix B | Intro to JAGS and BUGS | TBA |
| ⏳ | Ch. 6 | MCMC Diagnosis | TBA |
| ⏳ | Ch. 7 | Multivariate Gaussian | TBA |
| ⏳ | Ch. 8 | Selected topic: Bayesian Machine Learning | TBA |
| ⏳ | Ch. 9 | Selected topic: Modern Bayesian Computation | TBA |
Recommended Textbooks
Gelman, A., Carlin, J., Stern, H., Rubin, D., Dunson, D., and Vehtari, A. (2021). Bayesian Data Analysis, CRC Press, 3rd Ed.
Hoff, P.D. (2009). A First Course in Bayesian Statistical Methods, Springer.
McElreath, R. (2018). Statistical Rethinking: A Bayesian Course with Examples in R and Stan, CRC Press.