Mathematics 216: Applied Stochastic Processes

Mathematics 216: Applied Stochastic Processes (Spring 2002)

Instructor

Description

This is an introduction to stochastic processes without measure theory. We will cover the theory of discrete/continuous Markov Chains, some Martingales, and finally a bit of Brownian Motion and Stochastic Integration.

There will be weekly assignments as well as a take home Midterm Exam and a Final Exam.

Prerequisites

Familiarity with random variables (say as in Math 135) is required. Background in Linear Algebra would be nice as well. Students will do some programming (simple simulations) and should have access to software that can handle basic matrix computations.

Text(s)

Introduction to Stochastic Processes, by Greg Lawler (Chapman & Hall/CRC).

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Last modified: 18 October 2001