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: