Course Homepage: Spring 2003

Usually Offered: Alternating Spring Semesters

Purpose: To give a sound intuitive understanding of probability model building and random processes. Small-scale computer simulations are used throughout.

Current Textbook: Concepts in Probability and Stochastic Modeling, James J. Higgins and Sallie Keller-McNulty, Duxbury Press,1995.

 

Topics Covered	Chapters	Time
Basic Probability: Events and random variables, permutations, combinations, simulation, conditional probability, independence.	1	2 weeks
Discrete Random Variables: Distributions, expectations/moments, sampling, simulation.	2	1.5 weeks
Special Discrete Distributions: Uniform, binomial, geometric, negative binomial, Poisson distributions.	3	1 week
Markov Chains and Modeling: Queueing systems, steady-state distributions, absorbing states, and first passage times.	4	3 weeks
Continuous Models: Probability densities, simulating continuous random variables, special continuous distributions (normal, exponential, gamma).	5-6	2.5 weeks
Markov Counting and Queueing Processes	7	2 weeks
Other topics (e.g. scheduling, renewal processes)	-	2 weeks

The above textbook and course outline should correspond to the most recent offering of the course by the Statistics Department. Please check the current course homepage or with the instructor for the course regulations, expectations, and operating procedures.  

Contact Faculty: Edsel Peña, James Lynch
(Last Updated: July 11, 2008)