Introduces Bayesian statistical modeling from a practitioner's perspective. Covers basic concepts (e.g., prior-posterior updating, Bayes factors, conjugacy, hierarchical modeling, shrinkage, etc.), computational tools (Markov chain Monte Carlo, Laplace approximations), and Bayesian inference for some specific models widely used in the literature (linear and generalized linear mixed models). (Formerly AMS 206.)
5 terms
Other grades
University of California, Santa Cruz
STAT 206 at UCSC: average GPA 3.76 across 501 students. Grade distribution by term. Introduces Bayesian statistical modeling from a practitioner's perspective…
Average GPA: 3.76
Grade distribution records: 501 students across 5 terms.
| Grade | Students | Percent |
|---|---|---|
| A+ | 260 | 51.9% |
| A | 128 | 25.5% |
| A- | 16 | 3.2% |
| B+ | 17 | 3.4% |
| B | 5 | 1.0% |
| B- | 6 | 1.2% |
| C+ | 3 | 0.6% |
| C | 7 | 1.4% |
| F | 15 | 3.0% |
| P | 7 | 1.4% |
| NP | 2 | 0.4% |
| S | 28 | 5.6% |
| W | 7 | 1.4% |
Based on 501 student grade records across 5 terms and 1 professor.
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