MATH 143M: Numerical Analysis and Scientific Computing
San Jose State University
Development and comparison of important algorithms for scientific computing in terms of efficiency, accuracy and reliability. Topics include systems of linear equations-direct and iterative methods, least squares problems, eigenvalues and eigenvectors, numerical stability and error analysis. Substantial assignments using contemporary software packages and professional subprogram libraries. Prerequisite(s): MATH 39; and one of CS 22A, CS 46A, CS 49, or MATH 50 (each with a grade of "C-" or better). Or instructor consent. Allowed Declared Major: Mathematics major/minor or Computer Science.
Average GPA: 2.50
Grade distribution records: 438 students across 9 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 23 | 5.3% |
| A | 46 | 10.5% |
| A- | 25 | 5.7% |
| B+ | 44 | 10.0% |
| B | 57 | 13.0% |
| B- | 41 | 9.4% |
| C+ | 42 | 9.6% |
| C | 60 | 13.7% |
| C- | 29 | 6.6% |
| D+ | 12 | 2.7% |
| D | 14 | 3.2% |
| D- | 6 | 1.4% |
| F | 39 | 8.9% |
Based on 438 student grade records across 9 terms and 2 professors.
Instructors
- Mohammad Saleem 391 students, Average GPA 2.46
- Plamen Koev 47 students, Average GPA 2.85