MATH 433
Mathematical Modeling Spring 2021
Division III Quantitative/Formal Reasoning
This is not the current course catalog

Class Details

Mathematical modeling means (1) translating a real-life problem into a mathematical object, (2) studying that object using mathematical techniques, and (3) interpreting the results in order to learn something about the real-life problem. Mathematical modeling is used in biology, economics, chemistry, geology, sociology, political science, art, and countless other fields. This is an advanced, seminar-style, course appropriate for students who have strong enthusiasm for applied mathematics, data science, and collaborative teamwork.
The Class: Format: seminar; To afford students flexibility during the COVID pandemic, this course is taught online, largely asynchronously. There is no lecture component. Students will read research literature, work on structured and open-ended projects, and participate in synchronous small-group meetings with the instructor via videoconference. The vast majority of work in this course requires students to collaborate with each other.
Limit: 20
Expected: 20
Class#: 5367
Grading: yes pass/fail option, yes fifth course option
Requirements/Evaluation: Students will complete reading assignments, writing assignments, modeling activities, research projects, and will record several presentations to be shared with the rest of the class. To move towards a non-hierarchical, transparent, and egalitarian grading system, the instructor follows the policy of "ungrading." Over the course of the semester, students will develop a rubric to assess their own learning and will evaluate themselves according to this rubric.
Prerequisites: MATH 250; MATH 309 or similar; and some experience with computer programming (equivalent to CSCI 134 or MATH 307).
Enrollment Preferences: Professor's discretion
Distributions: Division III Quantitative/Formal Reasoning
QFR Notes: This course focuses substantially on using mathematical and statistical tools and frameworks to describe, predict, and understand real-world systems.

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