Catalog Course Description

A rigorous development of the basics of modern probability theory based on a self-contained treatment of measure theory. The topics covered include: probability spaces; random variables; expectation; convergence of random variables and expectations; laws of large numbers; zero-one laws; convergence in distribution and the central limit theorem; Markov chains; random walks; the Poisson process; and discrete-parameter martingales.

Fall Term

3 hours of Instructor presentation of course materials per week and 9 hours of Outside Work Hours per week.

Spring Term

3 hours of Instructor presentation of course materials per week and 9 hours of Outside Work Hours per week.