About This Course

In this connector course we will state precisely and prove results discovered while exploring data in Data 8. Topics include: probability, conditioning, and independence; random variables; distributions and joint distributions; expectation, variance, tail bounds; Central Limit Theorem; symmetries in random permutations; prior and posterior distributions; probabilistic models; bias-variance tradeoff; testing hypotheses; correlation and the regression model.


Prerequisite: One semester of calculus at the level of Math 16A, Math 10A, or Math 1A. - Co-requisite: Foundations of Data Science (COMPSCI / DATASCI / INFO / STAT C8)


The course textbook will be available on the course website. Lectures and the textbook will be closely related in content and sequence, though examples done in lecture might be different from those in the text.


Lecture sessions will be replaced by live video “synchronous” sessions on zoom at the time specified for the class (1-2 PM PDT on Monday, Wednesday, and Friday) and video lectures will be recorded and posted for students in incompatible time zones. The first 6 classes up to and including the class on September 6th will be live. The remaining classes will be prerecorded and uploaded to the class website. However, I will be available during class time on Mondays and Wednesdays to answer questions related to lecture material for that week. Discussion will be provided both in person on campus and online. (Tuesday and Thursday). While we will not take attendance during lecture, we highly encourage you to attend because they are amazing opportunities for you to develop problem-solving skills and ask clarification questions.


There will be a Piazza site for this class. We will post important announcements on Piazza so please check it regularly. We will not be using bCourses.

The Required Components of Your Work

All dates and times are with respect to the Berkeley time zone (Pacific Daylight Time). It is your responsibility to convert them to your time and complete submission by the deadline. - Weekly homework which will be done on paper and turned in on Gradescope. Homework will be posted each Monday evening and will be due the following Wednesday at 11:59 PM PDT regardless of which time zone you are in. In some weeks, there may be deviations from this due to exams, holidays, etc.; we will let you know. The homework assignments will be based on the lecture material covered the previous week. Homework is graded based on correctness. We encourage you to use plenty of support available and get started as early as possible. Homework assignments are written through Jypter Notebooks on Berkeley’s datahub. Students are encouraged to use the python code blocks to aid them in their homework assignments. Students submit their assignments through Gradescope. - 4 Quizzes which consist of some combination of textbook reading quizzes, including multiple-choice, true/false, or blank filling questions, to help you check your own understanding, and math questions that require written work. There will be two prior to the midterm and two after. - Midterm on Monday October 4 2021. Alternate exam times will be offered to accommodate students in various time zones. More details about the midterms will be announced later. - Final exam on Wednesday December 15 2021. Alternate exam times will be offered to accommodate students in various time zones. More details about the finals will be announced later.

Anyone caught cheating on a weekly quiz or exam will receive a failing grade and will also be reported to the University Office of Student Conduct. Any unauthorized redistribution of quiz or exam material to anyone or any online platform, during or even after the designated testing period, is not only academic dishonesty but also intellectual property infringement.


In the calculation of your overall score, we will drop

Course grades will be assigned using the following weights: 24% Assignments, 6% Quizzes, 30% Midterm, 40% Final. We will clobber your midterm score with your final score if doing so results in a higher grade.

The assignment of letter grades is as follows:

If you are taking the class pass-fail, the cutoff for passing is 70%

Comments and Suggestions

If you have any comments or suggestions, please feel free to send an email to me or the GSI. All feedback is welcome.

Late Submission

Late submission of homework will not be accepted under any circumstances, unless you have relevant university accommodations. If you have such accommodations, please provide the formal notification to me and your GSI before the end of the first week of classes. There will be no alternate due dates for assignments missed due to illness, other commitments, and so on. The drops are intended to cover those situations.

Collaboration and Integrity

Any assignment or exam submitted by you is presumed to be your own original work. While you areencouraged to work together on the lab and homework assignments, there is no value to you in copying someone else’s work.

The standard for what constitutes your “own original work” is that if asked, you should be able to convincingly explain out loud what you have written to the instructor or a GSI. As you work on assignments, you can talk to each other about the problems, but you need to get to the point where the answer is something you have internalized as something you, yourself, understand and can convincingly explain to someone else. If you are not clear about the expectations for completing an assignment or taking an exam, be sure to seek clarification from the instructor or GSI beforehand. Any evidence of cheating will be subject to disciplinary action, at minimum a failinggrade on the assignment or exam in question.

Stat 88 materials including exams and solutions are the intellectual property of the course developers. From the campus statement on Academic Integrity: “… students may not circulate or post materials (handouts, exams, syllabi, i.e. any class materials) from their classes without the written permission of the instructor.”

It is expected that you will work with integrity and with respect for other members of the class, just as the course staff will work with integrity and with respect for you.


If you need accommodations, please contact the Disabled Students Program so that your GSI and I can be officially notified of these. One of our GSIs acts as a DSP coordinator and will be in touch with you about making sure your accommodations are met. Prior to exams, we will provide a form for you to fill out if the originally scheduled exam time does not allow sufficient time for your accommodations.

Classroom Inclusivity and Campus Resources

We are all responsible for creating a learning environment that is welcoming, inclusive, equitable, and respectful. If you feel that these expectations are not being met, you can talk to me or seek assistance from a variety of other campus resources which are collected here

The purpose of academic accommodations is to ensure that all students have a fair chance at academic success. Disability, or hardships such as basic needs insecurity, uncertain documentation and immigration status, medical and mental health concerns, pregnancy and parenting, significant familial distress, and experiencing sexual violence or harassment, can affect a student’s ability to satisfy particular course requirements. Students have the right to reasonable academic accommodations, without having to disclose personal information to instructors.