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

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Kansas State University

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STAT 907 - Bayesian Statistical Inference