All University of South Carolina system institutions will be closed through the end of the spring semester. Columbia campus virtual instruction will continue through the conclusion of final exams in May. Details can be found on the coronavirus landing page.

# Department of Statistics

## STAT 535

535—Introduction to Bayesian Data Analysis. (3) (Prereq: STAT 511 and STAT 515 or equivalent, or CSCE 582 (= STAT 582)) Principles of Bayesian statistics, including: one- and multi-sample analyses; Bayesian linear models; Monte Carlo approaches; prior elicitation; hypothesis testing and model selection; hierarchical models; selected advanced models; statistical packages such as WinBUGS and R.

Sample Course Homepage: Recent Semester

Usually Offered: Spring Semesters, Even Years

Learning Objectives: By the end of the term successful students should be able to do the following:

• Understand the philosophy of Bayesian statistical modeling
• Understand Bayesian models for numerous common data analysis situations, including prior elicitation
• Use software such as R and BUGS to implement Bayesian analyses
• Understand basic principles of both conjugate analyses and MCMC-based Bayesian analyses

Current Textbook: Bayesian Methods (Second Edition), by Jeff Gill, Chapman & Hall/CRC Press, 2008.

 Topics Covered Time Review of Probability Concepts 1 week Bayes' Law and the Basic Bayesian Framework 1 week Bayesian Analyses for Basic One-Sample Models 1.5 weeks Bayesian Linear Models 1.5 weeks General Classes of Prior Distributions and Prior Elicitation 1 week Some Useful Monte Carlo Methods (along with use of R and BUGS) 1.5 weeks Assessing Model Quality 1.5 weeks Bayesian Hypothesis Testing 1 week Bayesian Analyses for Two- and k-Sample Models 1 week Hierarchical Bayesian Models 1 week Advanced Bayesian Models: Count Regression, Mixed Models,Models for Clustered/Longitudinal Data (Time permitting) 2 weeks

The above textbook and course outline should correspond to the most recent offering of the course by the Statistics Department. Please check the current course homepage or with the instructor for the course regulations, expectations, and operating procedures.

Contact Faculty: David Hitchcock