STAT 907 - Bayesian Statistical Inference

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.

Credits: (3)

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

When Offered:
Fall, odd years

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Kansas State University

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STAT 907 - Bayesian Statistical Inference