MTH 550   Probability and Stochastic Processes

Fall 2018

Instructor: Lubos Thoma                  
Office: Lippitt Hall 101               Tel: 874.4451
Class schedule: TuTh 2:00 - 3:15pm, Lippitt Hall 201

Description:   This is a graduate class in probability theory and random processes for students in mathematics, engineering, finance, and computer science. The purpose of the course is to present the basic concepts and techniques of probability theory as well as some of their applications. Emphasis will be placed on fundamental principles, thinking probabilistically, and methods and results of modern probability theory.

Topics will include: basic properties of probability measures, discrete and continuous random variables, distributions, random walks, generating functions, limit theorems, large deviations, Markov chains and Markov processes, branching processes, Poisson processes, martingales, Brownian motion. To illustrate the general theory the class will include many applications (taking into account interests of the audience) to mathematics (e.g. discrete mathematics, percolations), engineering (e.g. signal processing), computer science (e.g. analysis of random(ized) algorithms), and mathematical finance.

Textbook:     J. B. Walsh Knowing the odds: an introduction to probability Graduate Studies in Mathematics, American Mathematical Society, 2012, ISBN: 978-0-8218-8532-1.
                       Additional lecture notes will be distributed in class.

Links: current preprints in probability
Probability Theory and Related Fields
Electronic Journal of Probability
Random Structures & Algorithms
Finance and Stochastics
a list of probability journals

Prerequisites: (MTH435 or MTH437) and MTH451

Accommodations: Any student with a documented disability is welcome to contact me as early in the semester as possible so that we may arrange reasonable accommodations. As part of this process, please be in touch with Disability Services for Students Office at 330 Memorial Union, 401-874-2098.