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Data 89: Mathematical and Graphical Foundations of Probability

UC Berkeley, Fall 2026

Week 1 Announcement

Aug 27 · 1 min read

Welcome to Data 89 Fall 2026!

Please do the discussion preference form to help us assign you to a weekly Wednesday discussion section that works for you. Make sure you’re signed into your Berkeley email!

Please sign into PrairieTest and accept your course invitation. More info on Ed. If you’re a DSP student with exam accommodations, please be sure to accept your course invitation and submit your letter of accommodation to us through the DSP portal so the CBTF can honor your accommodations.

Take a look at the syllabus, which contains information on the majority of the course logistics. Please read through it thoroughly! Take special note of our scheduled exam times: evenings of Monday September 28th and Monday November 9th, and morning of Tuesday December 15th.

First lecture is today (Thursday) at 2pm in Li Ka Shing 245. To request an exemption to the no laptop policy, complete the laptop exemption form today. Josh’s professor OH start today in Gateway B1040 3:30-4:30pm right after lecture. Staff OH & tutoring opportunities coming soon.

Ask any questions on Ed, or send an email to data89@berkeley.edu

Calendar

Week 1

Thu, Aug 27

Homework 1 Probability Essentials

Lecture 1 Probability Essentials: Sets, Logic, and Algebra

Week 2

Mon, Aug 31
Tue, Sep 01	Lecture 2 Probability Essentials: 'Or' and 'Not' QuizPrereq Quiz (9/1 - 9/3)
Wed, Sep 02	Discussion 1Unions, intersections, and Complements
Thu, Sep 03	Lecture 3 Probability Essentials: 'If' and 'And'

Week 3

Mon, Sep 07	Homework 2Distributions and Models
Tue, Sep 08	Lecture 4 Probability Models: Discrete Random Variables QuizQuiz 1 (9/8 - 9/10)
Wed, Sep 09	Discussion 2Bayes Rule and Discrete Distributions
Thu, Sep 10	Lecture 5 Probability Models: Continuous Random Variables

Week 4

Mon, Sep 14	Homework 3Function Visualization Quiz RetakeQuiz 1 Retake (9/14 - 9/15)
Tue, Sep 15	Lecture 6 Visualizing Functions and Models: Global Properties
Wed, Sep 16	Discussion 3Visualizing Distributions
Thu, Sep 17	Lecture 7 Visualizing Functions and Models: Local Properties

Week 5

Mon, Sep 21	Homework 4Expectations QuizQuiz 2 (9/21 - 9/23)
Tue, Sep 22	Lecture 8 Distribution Attributes: Expectation as Central Tendency 1
Wed, Sep 23	Discussion 4Functions and Expectation
Thu, Sep 24	Lecture 9 Distribution Attributes: Expectation as Central Tendency 2

Week 6

Mon, Sep 28	Exam Midterm 1 Homework 5Variance and SD
Tue, Sep 29	Lecture 10 Distribution Attributes: Standard Deviation as Dispersion
Wed, Sep 30	Discussion 5Expectation and Variance
Thu, Oct 01	Lecture 11 Distribution Attributes: Tails and Asymptotics Quiz RetakeQuiz 2 Retake (10/1 - 10/2)

Week 7

Mon, Oct 05	Homework 6Tails, Asymptotics, and Series
Tue, Oct 06	Lecture 12 Techniques: Sequences, Series, and Asymptotic Rates
Wed, Oct 07	Discussion 6Asymptotics and Series QuizQuiz 3 (10/7 - 10/9)
Thu, Oct 08	Lecture 13 Techniques: Taylor Series and Function Approximation 1

Week 8

Mon, Oct 12	Homework 7Approximate and Limiting Chances Quiz RetakeQuiz 3 Retake (10/12 - 10/13)
Tue, Oct 13	Lecture 14 Techniques: Taylor Series and Function Approximation 2
Wed, Oct 14	Discussion 7Approximate and Limiting Chances
Thu, Oct 15	Lecture 15 Techniques: Integration by Parts

Week 9

Mon, Oct 19	Homework 8Integration Techniques
Tue, Oct 20	Lecture 16 Techniques: Integration by Substitution and Change of Variables
Wed, Oct 21	Discussion 8Integration Techniques QuizQuiz 4 (10/21 - 10/23)
Thu, Oct 22	Lecture 17 Coordinate Systems for Multiple Variables

Week 10

Mon, Oct 26	Homework 9Multiple Variables
Tue, Oct 27	Lecture 18 Visualizing Functions: Multivariate Functions
Wed, Oct 28	Discussion 9Working with Multiple Variables
Thu, Oct 29	Lecture 19 Probability Models: Joint Distributions Quiz RetakeQuiz 4 Retake (10/29 - 10/30)

Week 11

Mon, Nov 02	Homework 10Joint Density and Gradients QuizQuiz 5 (11/2 - 11/4)
Tue, Nov 03	Lecture 20 Techniques: Partial Derivatives and Gradients
Wed, Nov 04	Discussion 10Joint Densities and Gradients
Thu, Nov 05	Lecture 21 Techniques: Gradients and Optimization

Week 12

Mon, Nov 09	Exam Midterm 2 Homework 11Optimization and Double Integrals Quiz RetakeQuiz 5 Retake (11/9 - 11/10)
Tue, Nov 10	Lecture 22 Techniques: Integrals and Sums in Multiple Dimensions 1
Wed, Nov 11	Holiday - No Discussion
Thu, Nov 12	Lecture 23 Techniques: Integrals and Sums in Multiple Dimensions 2

Week 13

Mon, Nov 16	Homework 12Iterated Expectation and Integration on Manifolds QuizQuiz 6 (11/16 - 11/18)
Tue, Nov 17	Lecture 24 Techniques: Constrained Optimization
Wed, Nov 18	Discussion 11Double Integrals
Thu, Nov 19	Lecture 25 Techniques: Splitting Sums and Conditional Expectation

Week 14

Mon, Nov 23	Quiz RetakeQuiz 6 Retake (11/23 - 11/24)
Tue, Nov 24	Lecture 26TBA
Wed, Nov 25	Holiday - No Discussion
Thu, Nov 26	Holiday - No Lecture

Week 15

Mon, Nov 30	Homework 13Association QuizQuiz 7 (11/30 - 12/2)
Tue, Dec 01	Lecture 27 Techniques: Integration on Manifolds and Change of Coordinates
Wed, Dec 02	Discussion 12Iterated Expectation and Sums of Random Variables
Thu, Dec 03	Lecture 28 Application: Measuring Association
Fri, Dec 04	Discussion 13 Optional: Covariance and Correlation

Week 16

Mon, Dec 07	Quiz RetakeQuiz 7 Retake (12/7 - 12/8)
Tue, Dec 08	RRR Week
Wed, Dec 09	RRR Week
Thu, Dec 10	RRR Week

Week 17

Mon, Dec 14	Finals Week
Tue, Dec 15	Finals Week
Wed, Dec 16	Finals Week
Thu, Dec 17	Finals Week