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.
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
Introduction to Probability Models by Sheldon M. Ross.
Submitted by: David Bao
Date: September 13, 2012