MATH 120: OPTIMIZATION
University of California, Riverside
4 Units, Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): MATH 010A with a grade of "C-" or better; MATH 031 with a grade of "C-" or better. Introduction to classical optimization including unconstrained and constrained problems in several variables, Addresses Jacobian and Lagrangian methods and the Kuhn-Tucker conditions. Covers the basic concepts of linear programming including the simplex method and duality with applications to other subjects.
Average GPA: 3.04
Grade distribution records: 2,359 students across 30 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 287 | 12.2% |
| A | 386 | 16.4% |
| A- | 319 | 13.5% |
| B+ | 275 | 11.7% |
| B | 272 | 11.5% |
| B- | 193 | 8.2% |
| C+ | 136 | 5.8% |
| C | 191 | 8.1% |
| C- | 64 | 2.7% |
| D+ | 22 | 0.9% |
| D | 70 | 3.0% |
| D- | 15 | 0.6% |
| F | 86 | 3.6% |
| NP | 4 | 0.2% |
| S | 15 | 0.6% |
| W | 24 | 1.0% |
Based on 2,359 student grade records across 30 terms and 12 professors.
Instructors
- Hassan Attarchi 522 students, Average GPA 3.06
- Henry Tucker 270 students, Average GPA 3.03
- Ali Pakzad 160 students, Average GPA 3.08
- Qixuan Wang 157 students, Average GPA 3.17
- Zilong Song 150 students, Average GPA 3.05
- Kadriye Nur Saglam 65 students, Average GPA 3.00
- Yat Tin Chow 52 students, Average GPA 3.68
- Peter Samuelson 51 students, Average GPA 3.60
- Jonathan Dugan 30 students, Average GPA 2.84
- Amir Moradi Fam 28 students, Average GPA 3.70
- Dane Lawhorne 26 students, Average GPA 2.91
- Ethan Kowalenko 24 students, Average GPA 2.71