Summer 2026 (tentative) and Fall 2026
- Math 3200: Probability Theory
- This course is an integral part of the Data Science curriculum, providing the statistical foundation for modeling randomness and uncertainty in data. Students develop an understanding of probability as the framework underlying statistical modeling and inference. Through statistical reasoning, students learn how probability models describe random phenomena and support modern statistical methods used in data science.
- Catalog Description: Topics include: basic probability theory, combinatorial methods, independence, conditional and marginal probability, probability models for random phenomena, random variables, probability distributions, distributions of functions of random variables, mathematical expectation, covariance and correlation, conditional expectation, asymptotic distributions, and sampling distributions. The course makes use of the statistical program R to evaluate and graph probability models and distribution functions, and to simulate realizations of random variables.
