MAST 331
Mathematical Modelling
Winter 2026
Topics
- Introduction, what is math modelling? Units and nondimensionalization.
- Single variable optimization, sensitivity, and Newton’s method.
- Multivariable optimization and Lagrange multipliers.
- Shadow pricing, multivariate Newton’s method, linear programming.
- Dynamic models: steady-states, phase lines, phase planes.
- Phase plane sensitivity, difference equations, cobweb diagrams.
- Linear dynamical systems and Romeo + Juliet.
- Local linearization and Hartman–Grobman theorem.
- Computational aspects of dynamic models.
- Discrete and continuous probability models, intro to statistics.
- Intro to statistics, diffusion models, and Markov chains.
Readings
- Complete instructor notes on course topics.
- Reference (not explicitly required): Mark M. Meerschaert. Mathematical Modeling, 4th edition. Elsevier.
Winter 2022 · MAST 331
Readings
- Encounters with Chaos and Fractals, by Denny Gulick, 2nd Edition, Chapman & Hall CRC Press, 2012.
Sources
- Course catalogue ↗2026–2027
- Syllabus or course outline ↗Winter 2026
- Historical course outline ↗Winter 2024
- Historical course outline ↗Winter 2022
- Winter 2026 outline. Explicitly no assigned textbook; the course is based partly on Meerschaert.
- Historical source. Generic Textbook/References headings remain requirement-unspecified. Bibliographic editions and years are retained as printed; source inconsistencies may remain. Automated extraction with conservative filtering; distinct bibliography strings screened for false positives; entire syllabus not manually reviewed.
- Historical source. Generic Textbook/References headings remain requirement-unspecified. Bibliographic editions and years are retained as printed; source inconsistencies may remain. Automated extraction with conservative filtering; distinct bibliography strings screened for false positives; entire syllabus not manually reviewed.