Discrete Probability Concepts And Models

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Course Description

Fundamental concepts and tools for the analysis of problems under uncertainty, focusing on structuring, model building, and analysis. Examples from legal, social, medical, and physical problems. Topics include axioms of probability, probability trees, belief networks, random variables, conditioning, and expectation. The course is fast-paced, but it has no prerequisites.

Grading Basis

RLT - Letter (ABCD/NP)

Min

4

Max

4

Course Repeatable for Degree Credit?

No

Course Component

Discussion

Enrollment Optional?

Yes

Course Component

Lecture

Enrollment Optional?

No

This course has been approved for the following WAYS

Formal Reasoning (FR)

Does this course satisfy the University Language Requirement?

No

Programs

MS&E20 is a completion requirement for: