Course Policies: A detailed overview of course policies (including grading and assignments) can be found in the course syllabus.
This course is an introduction to discrete stochastic processes. We will see how to model real-world stochastic processes as simple, structured random systems, and how doing so gives us the power to draw remarkably precise, controlled conclusions about the macroscopic behavior of these chaotic processes. Topics covered include discrete and continuous time Markov Chains, Martingales, Poisson Processes, and some topics in Statistical physics. This is a rigorous, theoretical, proof-based course, but we will not require knowledge of measure theory.