Probabilistic Analysis

Course Description

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, random variables, distributions, conditioning, expectation, change of variables, and limit theorems. Prerequisite: multivariable calculus and some linear algebra.

Course Details

  • Intensive Study: Data Science
  • Limited Enrollment: No High School Summer College students. Please consider MS&E 20.
  • Unit Range: Graduate students often prefer to take the course for three units.


Multivariable Calculus and some Linear Algebra

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