A survey of discrete mathematical modeling techniques and their application to the natural and social sciences. Mathematical tools are selected from Monte Carlo simulation, queuing theory, Markov Chains, optimization, discrete dynamical systems, artificial intelligence, and game theory. Emphasis is on formulating models, investigating them analytically and computationally, and communicating the results.
Counts as an elective in the Data Science interdisciplinary minor.
Satisfies the Mathematical and Quantitative Thought distribution requirement.
Mathematics 140 or 150 or permission of the instructor. (Spring)