Curriculum
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Descriptions
EECS 302: Probabilistic Systems

Quarter Offered

Fall : 9-9:50 MTuWF ; Wei
Spring : 10-10:50 MTuWF ; Guo

Prerequisites

Math 234 and equivalent.

Description

Introduction to probability theory and its applications. Axioms of probability, distributions, discrete and continuous random variables, conditional and joint distributions, correlation, limit laws, connection to statistics, and applications in engineering systems.

May not receive credit for both 302 and any of the following: IEMS 202; MATH 310-1, 311-1, 314, 385; STAT 320-1, 383.

REFERENCE TEXTS: Sheldon Ross, A first course in probability, 9th Edition (Pearson, ISBN-10: 032179477X; ISBN-13: 978-0321794772)

COURSE INSTRUCTOR: Prof. Ermin Wei (Fall), Prof. Dongning Guo (Spring)

COURSE COORDINATOR: Prof. Ermin Wei

COURSE GOALS: To teach students the basic concepts of probability theory and statistics, random variables, conditional distributions, and correlation as they arise in engineering signal and systems models.

COMPUTER USAGE: Matlab Assignments

LABORATORY PROJECTS: None

COURSE OBJECTIVES: When a student completes this course, s/he should be able to:

• Understand the basic concepts of probability and how they arise in engineering systems.

• Analyze systems involving uncertainties using random variable models.

• Understand the concepts of distributions, correlation, and other averaging properties.

• Design simple reliable engineering systems in the presence of errors and failures.

• Understand the basic elements of statistics and analysis of data.

ABET CONTENT CATEGORY: 100% Mathematics