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MATH 457: Bayesian Statistics

Mathematics · 4 credits

Introduction to Bayesian inference; prior and posterior distributions; conjugate priors; statistical inference, including summarizing posterior information and making predictions; hierachical and linear regression models. Monte Carlo methods including Gibbs sampling.

Offered in 4 of the 26 listed terms (Spring 2021 to Spring 2027).

Prerequisites

MATH 342 and MATH 442

Prerequisite tree

Each course's own prerequisites, down to the first courses in the chain.

From Banner's catalog for Spring 2027. Banner lists only the requisites it enforces, so check the catalog entry too.

Required by (0)

No course lists it as a prerequisite.

Syllabi and course websites

None listed yet.

Instructors

InstructorSectionsTerms
Anderson, Amy3Spring 2021 to Spring 2027
Chan, Victor1Spring 2023

Every offering in the listed terms (4 sections)

TermSecCRNTypeMeetsInstructorEnrolledDelivery
Spring 2027023257LectureMTRF 1:00pm-1:50pm · MH 113Anderson, Amy0/30Face to Face Instruction
Spring 2025023097LectureMTRF 12:00pm-12:50pm · BH 317Anderson, Amy8/23Face to Face Instruction
Spring 2023023597LectureMTRF 1:00pm-1:50pm · BH 112Chan, Victor12/15Face to Face Instruction
Spring 2021023874LectureMTRF 1:00pm-1:50pm · REMOTE SYNCAnderson, Amy9/27Face to Face Instruction