Bayesian Theory and Methods I

Catalog description

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.