### Fall 2019

## General Course Information

### Learning Objectives

By the time the students successfuly complete the course, they should be able to:
- 1. Explain the foundations of probability theory, random variables, and stochastic processes.
- 2. Formulate and analyze probabilistic models and methods for
electrical and computer engineering problems.
- 3. Make precise statements about probabilistic models.

### Brief Course Description

- Probability theory
- Random variables
- Stochastic processes
- Examples from various applications.

### Text

### Prerequisites

- Undergraduate linear signals and systems.
- Undergraduate probability and statistics.
- An appreciation of rigor and abstract thinking.

### Grading

- Homework due every 2 weeks: 10%
- Three exams: 30% each
- Project: none

### Examples of applications

- Communication systems
- Manufacturing systems
- Internet
- Computer performance modeling
- Investment planning

### Contact information

Professor Edwin K. P. Chong
- E-mail: (preferred mode)
- Phone: 970-491-7858
- Fax: 970-491-2249

Course web pages:

Professor Edwin K. P. Chong,
This document was last modified
October 24, 2019.