Fundamental techniques for the numerical solution of problems in science and engineering: floating-point arithmetic, error analysis, root finding, numerical linear algebra, interpolation, numerical differentiation and integration, and the numerical solution of ordinary differential equations. Both theory and implementation are emphasized, with examples drawn from applied fields.
Prerequisites. MATH 2270 (Linear Algebra), MATH 2280 (Differential Equations), and experience programming in MATLAB, Python, or a similar language.
Slides are posted as PDFs after each lecture; a link goes live once the file is uploaded. Shaded rows mark homework due dates.
Topics are tentative and subject to change; updates will be announced in class and on Canvas.
Four assignments, 12% each. PDFs are posted here when assigned; solutions appear after the due date.
The exam paper and solutions are posted on USU Box after the exam; both require a USU sign-in to open.
Suggested textbooks. Numerical Analysis, 10th ed., Burden & Faires; and Numerical Methods: Design, Analysis, and Computer Implementation of Algorithms, Greenbaum & Chartier.
Software. MATLAB or Python (NumPy/SciPy/Matplotlib) is recommended for implementing algorithms and completing assignments.
The final project consists of a written report and a presentation on the implementation and analysis of a numerical method; details will be provided in class. No exams or quizzes will be given during No-Test Week (December 7–11).
| A | 93–100 | B– | 80–82 | C– | 70–72 |
| A– | 90–92 | C+ | 77–79 | D | 60–69 |
| B+ | 87–89 | C | 73–76 | F | 0–59 |
| B | 83–86 |