Statistics 251/551 (Spring 2009)

Stochastic Processes

Instructor: David Pollard
When: Mon, Wed 1:00 - 2:15
Where: WLH 119
Office hours: after each class, and Thursday 12:30-1:30
TA: Dan Campbell
Problem session: to be arranged if needed

Introduction to the study of random processes, including Markov chains, Markov random fields, martingales, random walks, Brownian motion and diffusions. Techniques in probability, such as coupling and large deviations. Applications to image reconstruction, Bayesian statistics, finance, probabilistic analysis of algorithms, genetics and evolution. After Statistics 241a or equivalent.

Intended audience

The course is aimed at students (both graduate and undergraduate) who are comfortable with introductory probability (as covered in Stat 241/541).


The course will be based on a book manuscript written by Joe Chang. I will take some material from each chapter. I will post supplementary notes if I deviate too far from Joe's treatment of any topic.

Topics (tentative)


The final grade will be based on the weekly homework plus two take-home exams.

Students who wish to work in teams (no more than 2 to a team) should submit a single a solution set. All members of a team will be expected to understand the team's solutions sufficiently well to explain the reasoning at the blackboard. Occasional meetings with DP will be arranged.

DBP 9 Feb 2009