CS109: Probability for Computer Scientists, Spring 2024

Announcements and Updates

  • Mon, Apr 22: The three student coordinators who manage much of the section leader program were in touch and asked I share the following:

    • Hello! We are the coordinators of the CS198 program (also known as section leading/being an undergraduate TA for CS106A/B)! If you're passionate about teaching, we encourage you to fill out the online application for CS198. You can find more info here!

    • The application is open now, and it is due on Thursday, April 25th at 11:59PM for students who have previously completed CS106B/X or equivalent and on Saturday, May 11th at 11:59PM for students currently enrolled in CS106B. More details on the position are located in the application.

    • Questions? Contact Emily, Diego, and Monica at cs198 at cs dot stanford dot edu.

  • Wed, April 3rd: Jessi Pipert, Associate Director of the Stanford Arts Institute, emailed me a few hours and asked if I might advertise a new minor in interdisciplinary arts that's open to all undergraduates, no matter their primary degree program. (I'm a huge fan of the arts and love the idea! In another life, I'd have majored in music and become a conductor 😇.)

    Check out this one page summary of the program to learn more.

This Week

Topic
Materials
Assignments
Optional Readings
Week 4
April 22
Lecture 10: The Normal Distribution
PSet 2 In
April 24
Lecture 11: Joint Distributions
PSet 3 Out
April 25
Section 3: Discrete and Continuous Random Variables
April 26
Lecture 12: Independent Random Variables
Ross: Ch 6.2-6.3,
Piech: Adding Random Variables

Schedule

Week 1
April 01
Lecture 1: Introductions
Piech: Counting
April 03
Lecture 2: Permutations and Combinations
PSet 1 Out
April 05
Lecture 3: Axioms of Probability
Ross: Ch 2.1-2.5, 2.7
Piech: Probability, Equally Likely Outcomes
Week 2
April 08
Lecture 4: Conditional Probability and Bayes Rule
April 10
Lecture 5: Independence
Ross: Ch 3.4-3.5
Piech: Independence
April 11
Section 1: Combinatorics and Probability
April 12
Lecture 6: Random Variables and Expectation
PSet 1 In, PSet 2 Out
Ross: Ch 4.1-4.4
Piech: Random Variables, Probability Mass Functions
Week 3
April 15
Lecture 7: Variance, Bernoulli, Binomial
Ross: Ch 4.5-4.6
Piech: Variance, Bernoulli, Binomial
April 17
Lecture 8: Poisson and Approximations
Ross: 4.7-4.10
Piech: Poisson
April 18
Section 2: Random Variables and Expectation
April 19
Lecture 9: Continuous Random Variables
Ross: Ch 5.1-5.3, 5.5
Piech: Continuous RVs
Week 4
April 22
Lecture 10: The Normal Distribution
PSet 2 In
April 24
Lecture 11: Joint Distributions
PSet 3 Out
April 25
Section 3: Discrete and Continuous Random Variables
April 26
Lecture 12: Independent Random Variables
Ross: Ch 6.2-6.3,
Piech: Adding Random Variables
Week 5
April 29
Lecture 13: Joint RV Statistics
Ross: Ch 6.4-6.5,
Piech: Correlation
May 1
Lecture 14: Conditional Expectation
Ross: CH 7.1-7.2
Piech: No assigned reading,
May 02
Section 4: Normal Distributions and Joint Distributions
May 03
Lecture 15: General Inference
PSet 3 In, PSet 4 Out,
Ross: No assigned reading,
Piech: Inference
Week 6
May 06
Lecture 16: Continuous Joint Distributions
Ross: Ch 6.1,
Piech: Continuous Joint Distributions
May 08
Lecture 17: Continuous Joint Distributions II
Ross: Ch 7.3-7.4,
Piech: no assigned reading
May 09
Section 5: Conditional Expectation
May 10
Lecture 18: Central Limit Theorem
Ross: Ch 8.3,
Piech: Central Limit Theorem

Note that all lectures and assignment deadlines are subject to change.

Our CS109 website imitates that used by University of Washington's CSE373, Spring 2019.