Prerequisite: STAT 544 or 554 or equivalent, or permission of instructor.
Course Description:Introduces decision theory and its relationship to Bayesian statistical inference. Students learn commonalities and differences between the Bayesian and frequentist approaches to statistical inference, how to approach a statistics problem from the Bayesian perspective, and how to combine data with informed expert judgment in a sound way to derive useful and policy relevant conclusions. Teaches necessary theory to develop firm understanding of when and how to apply Bayesian and frequentist methods, and practical procedures for inference, hypothesis testing, and developing statistical models for phenomena. Graphical models are introduced for constructing complex probability and decision models from modular components. as