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Instruction, Office Hours, and Help Sessions:

Lecture:

MWF, 11 am - 12 noon in Dwinelle 155

Instructor:

Shobhana Murali Stoyanov shobhana@berkeley.edu Office: 333 Evans Hall

GSIs:

Avani Kanungo Chuao Dong Oliver Maynard Tobias Roemer Xuanlin Mao Victor Ginsburg

Tutors:

Allen Ma Zhou Cynthia Xingdi Shi Ethan Juan Chant Jenny Gao Neha Rashmi Suresh

Office Hours:

You will find the list of office hours here, along with their locations. You may go to anyone’s office hour. In addition to these, the Student Learning Center also provides help for Stat 134.

Homework Parties:

Tutors and GSIs will offer “homework parties” (tutoring sessions) several times each week. You can go to these sessions to work on your assignments and recommended problems, or review topics that you have found confusing. You are welcome to attend any session that works for your schedule, and can find the hours and locations on the office hours page. These will be a great place to go and meet other students and collaborate on assignments with tutors and GSIs on hand to help you. The homework parties will begin next week, and will be on Mondays, Tuesdays, and Wednesdays, from 6-8 pm in Evans 340.

Jump to:

Overview

Our main text will be Introduction to Probability by Blitzstein and Hwang. We will cover most of this text (details in the schedule). You may also refer to Probability, by Pitman.

The course is an introduction to the ideas of probability, with no prior knowledge assumed. What is necessary is some degree of mathematical maturity, discussed further in the section on prerequisites.

The topics we will cover will include the axioms of probability, conditional probabilities, Bayes’ rule, discrete and continuous random variables and their distributions, independence of events, and independence of random variables, moments of distributions and moment generating functions, joint, marginal, and conditional distributions, conditional expectations, covariance and correlation, transformations of random variables, limit theorems including the CLT, Law of large numbers, tail probabilities, sampling. Maybe concentration inequalities, ideas of convergence, Markov chains.

We hope that you will learn how to think about uncertainty and randomness, and develop a strong mathematical foundation as you progress in your study of statistics and data science. Our goal is to equip you with the skills that you need to understand and solve difficult problems in statistical inference, and to appreciate the beautiful ideas in probability theory

Prerequisites

A year of calculus, so a level of ease with calculus is assumed.

Logistics and Attendance

Schedule

The list of topics to be covered and the corresponding chapters to be read will be published here a few weeks at a time, since it can be dynamic. Please do your best to complete the suggested readings before lecture, as it will make your comprehension in lecture much stronger.

Websites to bookmark:

Attendance and Lecture Recordings:

Lecture attendance is expected and encouraged, but not mandated or tracked.

Lecture recordings will only be available with requests made ahead of time, or under extenuating circumstances. Though lecture will be recorded using course capture, these recordings will not be released to everyone. Rather, they will be shared with students who have extenuating circumstances and who request it in advance.

For example, if you are not feeling well and cannot make it, this is a legitimate reason, but oversleeping and missing class is not. That said, every student will be entitled to two “free” recordings on request, with no reason needed. After that, you need to provide a better reason than just missing class.

You must make the request within a week of the lecture using the recording request form (link on bcourses). Requests made after a week will not be honored. Lectures missed due to late enrollment will be provided on request, without counting against the two free requests.

Discussion sections: You are expected to attend section, and you must attend the section that you are enrolled in. Attendance is tracked using discussion worksheets that are collected at the end of section. The worksheets are graded for completion and will be returned in the next section meeting. If you attend at least 80% of all the sections, this will contribute extra credit to your grade that will bump your grade to the next bin (for example, from B to B+). Quizzes will be administered in section, and we do not offer make ups.

Assessments

There are three types of assessments that we will administer in this course:

Homework assignments and discussion worksheets: As mentioned above, the discussion worksheets will be collected at the end of each section meeting and will be returned in the next section meeting. You will work in groups on the discussion worksheet during section. The worksheet will consist of problems from the text, and at least a few of them will closely resemble the homework. The worksheets will be graded for completion. We will have weekly homework assignments that will also be graded for completion. Homework will be due on Thursday beginning next week (Sept 4) at 11:59 pm. These assessments are essentially graded on effort. Each student will have two free extensions of two days each (I will post a form). Save them for true emergencies, since we will not accept late homework beyond that, unless you truly have extenuating circumstances (say, severe medical emergencies). For discussions, you may miss two discussions (and the worksheets) without question, but anything beyond that you will need to come see me and talk about why you are missing the discussions. You will miss turning in the worksheets, which will impact your grade. We will also drop the two lowest homework scores.

Quizzes: About every other Thursday, you will have quizzes in section, 6 quizzes in all. These quizzes will consist of a few multiple choice/ fill in the blank problems to test your understanding of basic concepts, and a few short problems based entirely on the homework (that is, the context might be changed, but the computations will be the same or similar to the homework you would have turned in the previous Thursday). The short answers and MC will test you on definitions, important results, and fundamental ideas from each topic. The quizzes test your proficiency. For a quiz to be counted as proficient, you will need at least 80% on the quiz. You will have an opportunity to retake each quiz once, and details of the retakes will be announced later. Retakes will not be offered for missed quizzes unless you have notified us ahead of time and we have excused your absence.

Exams: These will test your mastery. We will have three exams: two midterms in class on Wednesdays 10/1 and 11/5, and a comprehensive final exam (on 12/15 at 11:30), Each exam will be comprehensive. So, for example, the second midterm will be in two parts, and part 1 can clobber the first exam. The final will consist of three parts, with part 1 and part 2 able to clobber midterms 1 and 2 respectively. DSP students will need to arrange to take all the exams and quizzes with the DSP proctoring service. Exams test your mastery of the material. Note that you must take the final in order to pass the class.

Grades

Given the three components of your grade (effort, proficiency, and mastery),

Mechanism: Letter grades will be assigned via the standard scale, excepting specific adjustments (see below). Grades will be computed as detailed below:

Participation and Effort (Discussion + Homework): Completion percentage for discussion worksheets and HW, weighted 50% HW completion average, 50% discussion participation average.

Proficiency (quizzes): Any score at or above 80% (inclusive) is considered proficient. Any score at or above 60% but less than 80% is a semi-proficient. You may retake a quiz according to the retake policy if your quiz grade is not above 80%. Your score will be the better of your two quiz grades.

Mastery (exam): Your exam average will be computed with the following weights: at least 45% for your final exam, at least 30% for your midterm 2, and 25% for your midterm 1. Exams will not be curved. The “at least” is because of the clobber policy.

Final Grade:

Note that in order to pass the class, you must have:

If any of these three conditions is not met, you will not pass the class.

Your grade will equal your exam average, floored at the larger of the two letter grade floors set by participation and proficiency, and bounded above by the smaller of the two letter grade caps set by participation and proficiency. Grades based on exam averages will be assigned according to the standard scale. I don’t plan to curve your grades, but might move all the bins if I feel that the exams were too difficult. I never curve down, the point is always to improve the grades. The median in the class should fall around a B. If you are concerned about your grades, come and talk to me in office hours.

Conflicts, DSP accommodations, and the Honor Code

Scheduling conflicts:

Please email to notify your GSI and copy Prof. S, about any known or potential conflicts with the quizzes and exams. We will do our best to work with you, but cannot give you guarantees.

DSP Accommodations:

UC Berkeley is committed to creating a learning environment that meets the needs of its diverse student body including students with disabilities. If you anticipate or experience any barriers to learning in this course, please feel welcome to discuss your concerns with me.

If you have a disability, or think you may have a disability, you can work with the Disabled Students’ Program (DSP) to request an official accommodation. The Disabled Students’ Program (DSP) is the campus office responsible for authorizing disability-related academic accommodations, in cooperation with the students themselves and their instructors. You can find more information about DSP, including contact information and the application process here: dsp.berkeley.edu.

If you have already been approved for accommodations through DSP, please make sure that your GSI or I know this as soon as possible, since we need to arrange the proctoring. You will take all the quizzes and exams with the DSP proctoring service, which you will schedule yourself through your portal.

Academic Misconduct and Community Standards:

You are encouraged to discuss the homework problems with each other and the course staff. In fact, verbalizing your reasoning is known to deepen your understanding. However, please write up your solutions on your own as this will help cement your understanding. Homework parties will be a great place to talk through the problems with your colleagues, tutors and a GSI. We cannot police your use of GenAI, nor enforce any prohibitions, so though we will consider it short-sighted and foolhardy to rely on such tools to do your homework, but we will not consider it cheating.

You are a member of an academic community at one of the world’s leading research universities. One of the most important values of an academic community is the balance between the free flow of ideas and the respect for the intellectual property of others. Researchers don’t use one another’s research without permission; scholars and students always use proper citations in papers; professors may not circulate or publish student papers without the writer’s permission; and students may not circulate or post materials from their classes (handouts, exams, syllabi--any class materials) without the written permission of the instructor.

Any assignment submitted by you, with your name, is presumed to be your own original work. Finally, you should keep in mind that as a member of the campus community, you are expected to demonstrate integrity in all of your academic endeavors. The consequences of cheating and academic dishonesty—including a formal discipline file, possible loss of future internship, scholarship, or employment opportunities, and denial of admission to graduate school—are simply not worth it.

For further reading, please reference Berkeley’s Principles of Community and the Berkeley Campus Code of Student Conduct.

Acknowledgements:

Parts of this syllabus, especially the sections on assessments and grading, were adapted from Alexander Strang’s 2025 summer course.

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