STAT 907 - Bayesian Statistical Inference

Credits: 3

Principles of Bayesian inference. Methods of Bayesian data analysis with applications in the sciences. Hierarchical and non-hierarchical models, including linear and generalized linear models. Model checking, Model selection, Model comparison. Bayesian computation including Markov Chain Monte Carlo algorithms. Applications in the sciences utilizing computer software.

Requisites:
Prerequisite: STAT 720 and STAT 771, plus one introductory course in statistical computing (e.g. STAT 725 or STAT 726 or equivalent background).

Typically Offered
Fall, odd years

Kansas State University

Course Catalog

STAT 907 - Bayesian Statistical Inference