Lecture, three hours; discussion, one hour. Requisites: courses 32B, 33A, 131A. Not open to students with credit for course 170E, Electrical and Computer Engineering 131A, or Statistics 100A. Rigorous presentation of probability theory based on real analysis. Probability space, probability and conditional probability, independence, Bayes' rule, discrete and continuous random variables and their distributions, expectation, moments and variance, conditional distribution and expectation, weak law of large numbers. P/NP or letter grading.

Review Summary

Clarity
3.3 / 10
Organization
6.7 / 10
Time
0-5 hrs/week
Overall
3.3 / 10

Reviews

    Quarter Taken: Fall 2021 In-Person
    Grade: N/A

    First quarter that the instructor was teaching

Course

Instructor
Aaron Palmer
Previously taught
21F

Grading Information

  • No group projects

  • Attendance not required

  • 2 midterms

  • Finals week final

  • 100% recommend the textbook

Previous Grades

Grade distributions not available.