#### Prerequisites & Bulletin Description

#### Course Objectives

Students will learn to:

- Calculate conditional probability, conditional expectation, and conditional variance.
- Define Markov Chains and do calculations based on them.
- Define Exponential and Poisson Processes and use them in applications.
- Define Continuous Time Markov Chains and do calculations based on them.
- Define M/M/1 Queues, M/G/1 Queues, and G/M/1 Queues, and use them in applications.

#### Evaluation of Students

Students will demonstrate their mastery of the course objectives on frequent graded homework assignments, quizzes, exams, and a final exam.

#### Course Outline

The order in which we work on the following topics may vary.

- Conditional Probability
- Conditional Expectation
- Conditional Variance
- Markov Chain
- Exponential Process
- Poisson Process
- Continuous Time Markov Chain
- Queuing Theory

#### Textbook

*Introduction to Probability Models* by Sheldon M. Ross.

Submitted by: David Bao

Date: September 13, 2012