Course Description
Introduction to Bayesian inference; specifying prior distributions; conjugate priors, summarizing posterior information, predictive distributions, hierachical models, asymptotic consistency and asymptotic normality. Markov Chain Monte Carlo (MCMC) methods and the use of exising software(e.g., WinBUGS).
Fall 2025
Instructors
Meeting Patterns
Classes Start:
August 18, 2025
Classes End:
December 2, 2025
Location:
01108 SAS Hall
Class Days:
M W
Class Start Time:
1:30pm
Class End Time:
2:45pm
Class Type:
Lecture
Credits:
3.00
Restrictions:
Prerequisite: ST 702 R: 17STPHD Students Only