STAT 170: REGRESSION ANALYSIS
University of California, Riverside
4 Units, Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 107; STAT 156B or STAT 160B; or equivalent. Topics include simple and multiple linear regression, scatter-plots, and point and interval estimation. Addresses prediction, testing, calibration, interpretation, and practical applications of multiple regression. Explores simple, partial, and multiple correlation; variable selection methods; diagnostic procedures; and regression for longitudinal data.
Average GPA: 3.29
Grade distribution records: 333 students across 6 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 10 | 3.0% |
| A | 102 | 30.6% |
| A- | 52 | 15.6% |
| B+ | 46 | 13.8% |
| B | 59 | 17.7% |
| B- | 20 | 6.0% |
| C+ | 10 | 3.0% |
| C | 11 | 3.3% |
| C- | 6 | 1.8% |
| D+ | 5 | 1.5% |
| D | 6 | 1.8% |
| D- | 2 | 0.6% |
| F | 3 | 0.9% |
Based on 333 student grade records across 6 terms and 2 professors.
Instructors
- Xinping Cui 164 students, Average GPA 3.38
- Esra Kurum 62 students, Average GPA 2.49