IE 569: Stochastic Simulation

Course Description

Stochastic simulation is the use of a computer simulation to generate artificial data and to then analyze that data as if they were the result of a statistical experiment. It is widely used to estimate the performance and effectiveness of all sorts of systems. While other courses on simulation focus on modeling, this course focuses on topics that are key in this sort of simulation, including:

Application areas will depend on the specific interests of the students in each offering. Students are expected to complete a simulation study in an area of their own choosing.

Intended Students: Those who intend to use stochastic simulation in research or on the job to determine reasonable estimates of system behavior.

Expected Background: The student should have at least a first course in calculus-based probability and statistics. Knowledge of queueing theory or stochastic processes would be helpful, but not necessary. Previous courses in simulation modeling may also be helpful, but not required.


Instructor: John Mullen, Tel: (575) 646-2958,
Texts: Simulation Modeling and Analysis, 4th ed., by Averill M. Law and Associates. 2007. ISBN: 0-07-329441-1
Reference: Simulation with Arena (with CD-ROM), 3rd. ed., by David Kelton, et. al. 2004. ISBN 0-07-291981-7.
  • Web-CT Site:
  • MatLab (required)
  • Arena (optional)
  • OPNET IT-Guru (optional)
  • MiniTab (optional)

Revision Date: November 13, 2008 by jpm.