Probability Theory I

4 credits

This is the first course in a three-course sequence in probability theory. Topics covered in the sequence include the measure-theoretic foundations of probability theory, independence, the Law of Large Numbers, convergence in distribution, the Central Limit Theorem, conditional expectation, martingales, Markov processes, and Brownian motion. Recommended preparation: completion of real analysis equivalent to MATH 140A-B strongly recommended. Prerequisites: graduate standing.