PSTAT 100: DS_CONC&ANLS
University of California, Santa Barbara
Overview of data science key concepts and the use of tools for data retriev al, analysis, visualization, and reproducible research in preparation for a dvanced data science courses. Topics include an introduction to inference a nd prediction, principles of measurement, missing data, and notions of caus ality, statistical traps, and concepts in data ethics and privacy.
Average GPA: 3.53
Grade distribution records: 1,361 students across 14 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 51 | 3.7% |
| A | 549 | 40.3% |
| A- | 303 | 22.3% |
| B+ | 184 | 13.5% |
| B | 121 | 8.9% |
| B- | 59 | 4.3% |
| C+ | 30 | 2.2% |
| C | 26 | 1.9% |
| C- | 10 | 0.7% |
| D+ | 2 | 0.1% |
| D | 10 | 0.7% |
| F | 16 | 1.2% |
Based on 1,361 student grade records across 14 terms and 6 professors.
Instructors
- Ruiz T D 397 students, Average GPA 3.62
- Baracaldo Lan 279 students, Average GPA 3.25
- Abuzaid A H 217 students, Average GPA 3.78
- Zhang T 197 students, Average GPA 3.25
- Marzban E P 140 students, Average GPA 3.52
- Franks A 131 students, Average GPA 3.83