Mathematical models describe a variety of real-world situations, providing unique information and insight. Systems that can benefit from modeling range from daily occurrences (e.g. optimizing campus parking) to highly complex interactions (e.g. predicting weather) to currently theoretical scenarios (e.g. computing the best vaccination or treatment strategy in case of bioterrorist attack).

Mathematical modeling is a mathematical tool for solving real world problems. In this course, students study a problem-solving process. They learn how to identify a problem, construct or select appropriate models, figure out what data needs to be collected, test the validity of a model, calculate solutions and implement the model. Emphasis lies on model construction in order to promote student creativity and demonstrate the link between theoretical mathematics and real world applications.

Throughout this semester, we study a variety of modeling types. Topics include proportionality models, fitting models to data, creating simulations, dimensional analysis, probabilistic modeling, optimization, and both discrete and continuous models. For day-to-day details, see the calendar pages of our class website.

Additionally, students work in small groups on a semester-long modeling project. Early-semester activities include discussions of possible project ideas, a workshop on technical writing, project proposals, and brief presentations in class. Later activities include individual group meetings, peer-reviewed rough drafts, and longer final presentations to the class.