PSTAT 115: BAYES DATA ANALYSIS
University of California, Santa Barbara
An introduction to the Bayesian approach to statistical inference, its theo retical foundations and comparison to classical methods. Topics include par ameter estimation, testing, prediction and computational methods (Markov Ch ain Monte Carlo simulation). Emphasis on concepts, methods and data analysi s. Extensive use of the R programming language and examples from the social , biological and physical sciences to illustrate concepts.
Average GPA: 3.06
Grade distribution records: 1,275 students across 19 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 36 | 2.8% |
| A | 319 | 25.0% |
| A- | 150 | 11.8% |
| B+ | 162 | 12.7% |
| B | 222 | 17.4% |
| B- | 86 | 6.7% |
| C+ | 68 | 5.3% |
| C | 121 | 9.5% |
| C- | 38 | 3.0% |
| D+ | 5 | 0.4% |
| D | 18 | 1.4% |
| D- | 8 | 0.6% |
| F | 42 | 3.3% |
Based on 1,275 student grade records across 19 terms and 5 professors.
Instructors
- Franks A 584 students, Average GPA 3.19
- Wainwright B 402 students, Average GPA 3.12
- Baracaldo Lan 112 students, Average GPA 2.44
- Targino R D 101 students, Average GPA 2.90
- Sun Y 76 students, Average GPA 2.93