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STAT 206BIntermediate Bayesian Inference

5 creditsGraduateStudent Option

Bayesian statistical methods for inference and prediction including: estimation; model selection and prediction; exchangeability; prior, likelihood, posterior, and predictive distributions; coherence and calibration; conjugate analysis; Markov Chain Monte Carlo methods for simulation-based computation; hierarchical modeling; Bayesian model diagnostics, model selection, and sensitivity analysis. (Formerly AMS 206B.)

Prerequisites

Prerequisite(s): STAT 203. Enrollment is restricted to graduate students. Undergraduates may enroll by permission (STAT 131 and 132 have to be verified by the instructor directly with the student).

Find a section and add it to your scheduleLive seat counts, time-conflict checks and the walk from your previous class.

When it runs

Winter 2027Open Winter 2027

SectionTypeWhenWhereInstructorSeats
01LectureAsynchronousStaffOpen 0/10

Winter 2026Open Winter 2026

SectionTypeWhenWhereInstructorSeats
01Lecture
Tue Thu 11:40am–1:15pm
Merrill Acad 002J. LeeClosed 10/10

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