Math 350 - Simulation analysis of random processes

Spring 2010


instructor	phone #	office	e-mail
Renato Feres	5-6752	Cupples I, 17	feres@math.wustl.edu

Subject: Real phenomena are often described mathematically by probabilistic models such as Markov chains and other related stochastic processes. This course is an introduction to techniques for the analysis of probabilistic models by use of numerical simulation. Course work will involve both theoretical and computer assignments. Prerequisite: Math 233. Familiarity with basic concepts in probability and statistics at the level of Math 2200 is strongly recommended.

Text: Simulation, by Sheldon M. Ross. Academic Press, third edition, 2001.

Tentative list of topics:

Elements of probability;
Generation of random numbers and discrete and continuous random variables;
statistical analysis of simulated data;
Introduction to Markov chain Monte Carlo methods;
Additional topics as time permits.

Coursework: Grades will be based on homework assignments and computer projects.