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STA 6352: Bayesian Theory and Methods I

Spring 2027 · 3 credit hours · 1 section · 15 open seats as of Oct 30, 2026, 4:05 AM Central

Prerequisite(s): STA 5353 or equivalent. This course introduces the principles of Bayesian statistical inference, covering foundational concepts, decision theory, prior construction, and posterior computation. Students will explore Bayesian methods for point and interval estimation, contrasting them with frequentist approaches, along with other key inferential techniques. Practical aspects of Bayesian computation, including modern computational techniques and their implementation, are also introduced.

Professors teaching STA 6352 in Spring 2027

John W. Seaman. See their BUBooks scores and reported grades in the builder.

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