Academic Catalog

STAT565 DECISION THEORY AND BAYESIAN ANALYSIS

Course Code: 2460565
METU Credit (Theoretical-Laboratory hours/week): 3(3-0)
ECTS Credit: 8.0
Department: Statistics
Language of Instruction: English
Level of Study: Graduate
Course Coordinator: Prof.Dr. VLDA PURUTUOLU
Offered Semester: Fall or Spring Semesters.

Course Content

Introduction to decision making. Subjective and frequentist probability. Bayes theorem and Bayesian decision theory. Advantages of using a Bayesian approach. Likelihood principle, prior and posterior distributions, conjugate families. Inference as a statistical decision problem. Bayesian point estimation, Tests and confidence regions, model choice, invariance, equivariant estimators, hierarchical and empirical Bayes extensions, robustness and sensitivity, utility and loss, sequential experiments, Markov Chain Monte Carlo Methods, Metropolis-Hastings Algorithm, Gibbs Sampling, The EM Algorithm.