STA 145

Bayesian Statistical Inference

Subjective probability, Bayes Theorem, conjugate priors, non-informative priors, estimation, testing, prediction, empirical Bayes methods, properties of Bayesian procedures, comparisons with classical procedures, approximation techniques, Gibbs sampling, hierarchical Bayesian analysis, applications, computer implemented data analysis.

Units: 4.0

Hours: Lecture—3 hour(s); Laboratory—1 hour(s).