AMS221: Bayesian Decision Theory

Explores conceptual and theoretical bases of statistical decision making under uncertainty. Focuses on axiomatic foundations of expected utility, elicitation of subjective probabilities and utilities, and the value of information and modern computational methods for decision problems. Prerequisite(s): course 206. Enrollment restricted to graduate students.

5 credits

Year	Fall	Winter	Spring	Summer

While the information on this web site is usually the most up to date, in the event of a discrepancy please contact your adviser to confirm which information is correct.