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. MATLAB codes used in class are linked under the lecture they go with (folder matlab/ in the course repository). Orange rows mark homework due dates; blue rows mark the in-class midterm and the final project presentations.
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 midterm is a 50-minute in-class exam on Fri, Oct 30, held during the regular class meeting in Old Main 207.
The practice midterm and its solutions are posted here before the exam. The exam paper and solutions are posted on USU Box after the exam; both require a USU sign-in to open.
Each student chooses one of the three projects below and submits a written report with MATLAB code. Presentations take place in class during the last three class meetings: Mon, Dec 7; Wed, Dec 9; and Fri, Dec 11. The report and code are due Fri, Dec 18, 11:59 p.m., on Canvas.
Q1.m, Q2.m, Q3.m) that produces its figures and tables, and a short README file.Each project is graded out of 100 points: three problems (70), code (10), written report (10), and presentation (10), with a 10-point bonus problem. See the project PDFs for details.
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 must be done in MATLAB.
The final project consists of a written report with MATLAB code and an in-class presentation; see Final project for the three projects and the requirements. Presentations take place during the last three class meetings (Dec 7, 9, and 11), and the report is due Dec 18. 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 |