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MATH 557: Bayesian Statistics
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).
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Prerequisites
None that Banner enforces.
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
| Instructor | Sections | Terms |
|---|---|---|
| Anderson, Amy | 3 | Spring 2021 to Spring 2027 |
| Chan, Victor | 1 | Spring 2023 |
Every offering in the listed terms (4 sections)
| Term | Sec | CRN | Type | Meets | Instructor | Enrolled | Delivery |
|---|---|---|---|---|---|---|---|
| Spring 2027 | 0 | 23268 | Lecture | MTRF 1:00pm-1:50pm · MH 113 | Anderson, Amy | 0/30 | Face to Face Instruction |
| Spring 2025 | 0 | 23098 | Lecture | MTRF 12:00pm-12:50pm · BH 317 | Anderson, Amy | 2/12 | Face to Face Instruction |
| Spring 2023 | 0 | 23598 | Lecture | MTRF 1:00pm-1:50pm · BH 112 | Chan, Victor | 2/15 | Face to Face Instruction |
| Spring 2021 | 0 | 23875 | Lecture | MTRF 1:00pm-1:50pm · REMOTE SYNC | Anderson, Amy | 3/8 | Face to Face Instruction |