Prerequisite: ST 522
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).
| SECTION | INSTRUCTOR | BUILDING | TIME | DAYS | AVAILABILITY | ENROLLMENT |
|---|---|---|---|---|---|---|
| 001 | 01216 SAS Hall | 10:15AM-11:30AM | MW | AVAILABLE | 40/40 - Closed |
