Syllabus: Fall 2026

Stat 20: Introduction to Probability and Statistics

Welcome to the Age of Data, where claims made using data are all around us: in the news, in the pages of scientific journals, in the policies of government, and in the board rooms of companies across the world. In this course you will explore the forms of claims that are made using data. Some of these are subtle claims about the structure of the data at hand. Others are grand claims about scientific truths or predictions of what will happen in the future. This course will train your ability to critique and construct such arguments made using data.

Instructor	Email
Adam Lucas	alucas@berkeley.edu
Andrea Massari	amassari@berkeley.edu
Jeremy Eli Sanchez	jeremysanchez@berkeley.edu
Gaston Sanchez Trujillo	gasigiri@berkeley.edu
Shobhana Stoyanov	shobhana@berkeley.edu
Everett Wetchler	wetchler@berkeley.edu

What you will learn:

The course mission is to teach you to “construct and critique claims made using data.” What does that mean? Roughly:

Working with uncertainty, and quantifying it (statistics, probability)
Writing computer code in the R language to analyze data (R is widely used in research, especially in academia)
Most importantly, how to use all of this to investigate questions you are interested in.

Semester-start logistics:

The course website is your best friend

Bookmark it. It has everything. https://stat20.berkeley.edu/fall-2026/

Waitlisted?

Come to class, and do the work, while on the waitlist. You’ll be expected to be up to speed if and when you get into the class.
Instructors have no control over the waitlist. Please don’t ask us for permission codes, etc. The administration controls the waitlist, manages priorities and rules, and lets people in when they can.
Unfortunately we don’t know your chances of getting in off the waitlist! Make a backup plan, and come to class in the meantime.

Joining class after we’ve gotten started?

This course moves fast, so after two weeks into the semester, you’ll have too much material that you’ll need to make up, so you will have to wait to a subsequent semester to take Stat 20.

If you join late, but within the first 2 weeks:

Read the syllabus (this document) - it answers a LOT of questions.
Catch up on the notes, tutorials, slides, and assignments on the main course webpage. The first two weeks of material are very important so you must be able to make up assignments.

Final exam date / conflicts

Our final exam is Thursday, December 17, from 7-10pm.
We will offer an alternate time to those with conflicts, very likely Friday morning, December 18, 8-11am. We’ll communicate thoroughly with you about this. We have to wait until closer to the exam to know with certainty when we can have the alternate final.
Exam locations are not set until much closer to the exam, so stand by for that too.

Classes are not recorded, and we don’t allow time conflicts.

That’s all we have to say about that.

How this class works, in brief

Course Vibes

This course is designed for students who have never done statistics or have done any type of computer programming before! There are no stupid questions, and we will not tolerate behavior which discourage students from asking questions. Everyone starts somewhere.

We aim to make class warm and collaborative. If you ever find class discouraging or intimidating, let us know. Reach out to your instructor, we’ll try to improve things for you.

Because this class is so collaborative / group-oriented, people often make friends in class. This is a non-grading perk of just showing up. In this big anonymous university, it helps to have small-group work to meet people you might like.

Read. Before. Class.

This is a “flipped class” - you are expected to do the assigned readings before coming to class. This way, we can keep lecture light and focus most of the time on doing hands-on work. If you don’t read ahead of time, this whole approach breaks down.

Why do it this way? Research shows that this is a more efficient way to learn, especially for things like math and coding where you need a lot of hands-on “doing” time to fully comprehend it. In theory it goes like this: you read at home, you sort of get it, then you come to class, work on DOING things (with our help on hand), and then you really get it.

Monday, Wednesday, and Friday

First, IGNORE the lab/lecture distinction you see on CalCentral. Just think of the class as having: a Monday class for one hour, and Wednesday/Friday classes for two hours each.

Wednesday and Friday are “normal” class days. We meet for two hours, and most of that time is hands-on working. There isn’t a split into one hour of lecture and one hour of lab - it’s just a single two-hour block.

Mondays may vary in content (your instructor will tell you), but the default is generally extra office hours / tutoring. That is, you can come and do your work and we will be there to help you. Attendance is optional on Mondays, but required on Wed/Fri (see “Attendance” section below).

Assignments and Grading

Grading Rubric (Overall)

There are a lot of small, low-stakes assignments in this class. For most types, we will automatically drop one or more of your lowest scores. The “drops” are only meant to cover brief absences, illness, and other unexpected circumstances. They’re not meant to cover for bombing assignments. See the table for details:

Assignment Type	Percentage	Count (estimate)¹	# Drops
Reading Questions	3%	26	4
Attendance (W/F)	7%	27	4
Worksheet Packets	10%	14	2
Labs	10%	14	2
Capstone Project	10%	1	0
Quizzes²	30%	4	1
Final Exam	30%	1	0

You will see all assignments, and when they are due, on the main class webpage.

¹ We may add/remove assignments as needed during the semester.

² You can retake any and all quizzes (one time each). More details below.

Also:

Grade buckets are standard. That is, 97%+ is an A+, 93-96 is an A, 90-93 A-, 87-89 B+, and so forth.
Curving: in general, we do not curve the course. However, if the final grade distribution is too low (meaning our exams were harder than intended), we may move all grades upward. Consult Berkeleytime for previous grading distributions, and do not ask group tutors about grading (they do not grade your assignments).

Attendance

Most of class time is hands-on work time with skilled helpers at the ready. Your instructor, and a team of several undergraduate tutors, will be standing by to help as you work. This is by far the best way to learn. Hence, we will have a mechanism for tracking attendance, as a small part of your grade.

Attendance is only tracked on Wednesday and Friday (the 2-hour-long classes). Attendance is encouraged but not required on Mondays.

On W/F you have to be on time and stay through the full class to get credit for attendance. Please don’t try to gamify this. Coming to class is good for you, so just show up.

Reading Questions (due the night before EVERY Wed/Fri class)

Our “textbook” is entirely online, on the course website. Generally, each wed/fri class has an accompanying set of notes and a “tutorial” (generally focused more on coding).

Like we said, this is a “flipped” class. That means you are expected to read the notes/tutorials beforehand. You may not fully understand it, but you are expected to at least complete a small set of 5 simple “reading questions” (on Gradescope) by midnight the night before each W/F class.

Why? Research shows that you learn better if you are exposed to material multiple times (first in reading, then again in class, and again studying for quizzes). Further, you learn better by doing, with help available, so that’s what class time is mostly for.

Quiz Information (IMPORTANT)

Four times this semester, you’ll have a quiz. These will not be done in class! Instead, we are using Berkeley’s relatively new computer testing facility (CBTF).

We will walk you through how to do it, in class, but here’s the general idea:

For each quiz, you will sign up for a time slot through an online portal. Typically time slots for a quiz span a few days, so you have some choice when you take it. Students will take the quiz when it suits their schedule, not all at once.
At the appointed time, you’ll go to the CBTF facility, in Moffitt 175. You’ll complete the quiz on a computer. You cannot bring anything besides water into the facility. Scratch paper will be provided.
Grades should be ready quickly, depending on the amount of hand-grading required for each quiz.
Quiz questions are semi-randomized, to prevent cheating and information leakage. You won’t get identical questions to everyone else, but they will be equivalent in content and difficulty.

YOU CAN RETAKE ANY QUIZ

Research shows that people learn better when they study material multiple times, spread out over time. And sometimes you just don’t do as well on a quiz as you’d hoped. In that light, each quiz comes with a chance to re-take it (once). It won’t be exactly the same quiz, but it will be similar and cover the same content.

Logistics: You can sign up for a “retake” version of any and all quizzes. Retakes are generally available for 1-2 weeks after the initial quiz. We will average your original quiz score with the retake score. However, these retakes cannot hurt you, so if your retake score is lower, we’ll ignore it and keep your original score only.

Here is the tentative schedule of quiz windows - this information is also on the main homepage:

Name	Duration	Open date	Close date	Reservations open:
Quiz 1	50min	Tue 09-08	Fri 09-11	Tue 09-01
Quiz 1 Retake	50min	Mon 09-14	Fri 09-25	Wed 09-12
Quiz 2	50min	Mon 09-28	Fri 10-02	Mon 09-26
Quiz 2 Retake	50min	Mon 10-05	Fri 10-16	Wed 10-03
Quiz 3	50min	Mon 10-19	Fri 10-23	Mon 10-16
Quiz 3 Retake	50min	Mon 10-26	Fri 11-06	Wed 10-24
Quiz 4	50min	Thu 11-19	Tue 11-24	Mon 11-07
Quiz 4 Retake	50min	Mon 11-30	Fri 12-04	Thu 11-25

You can see, for example, that Quiz 1 is taken sometime during the third week of class (Sep 8-11), and you can sign up for a timeslot beginning September 1. Retakes for Quiz 1 are available during the following two weeks (Sep 14-25), and you can sign up for a retake starting September 12. In other words, the day after one quiz window closes, the next one opens for sign ups.

All quizzes are 50 minutes long. If you have extra time through DSP, you’ll be granted it at the test facility, so don’t worry that it says “50 minutes” – you’ll get your allotted time when you show up.

SPOTS FILL UP so sign up early. There are plenty of spots for everyone, but your ideal time may fill up. We do not offer exceptions or extensions for students who forget to book a quiz slots or don’t show up for a timeslot they booked.

What if I miss the initial quiz? Can I just do the retake? Not exactly. If you miss the original quiz, your score will be a zero. You can do the retake, but your score will be averaged with that initial zero. You’ll end up with something between 0% and 50%. This is better than nothing, and probably good practice, but we’re not offering retakes as an “alternate” quiz time.

Even after all the retakes, we drop everyone’s lowest quiz score. See the earlier overall grading rubric.

Worksheets and Labs

Nearly every class day, we will hand out a physical sheet of paper (a “worksheet”) with problems to work on.

You usually will be able to complete worksheets during class, but they aren’t due the same day - you have some time to take them home to finish if you need to.
You will submit them online through gradescope, by using your phone to “scan” the worksheet to a PDF first.
You may work in groups if you like, but each person has to submit their own work (see “Group Work, Individual Submissions” section below)
Because there are so many, we bundle worksheets into “worksheet packets.” So a “worksheet packet” submission might have 2 or 4 worksheets in it. We’ll be clear about what sheets are in a packet and when it is due.
Blank worksheets are always available online in case you miss a class day. You can either print and complete it, or just work on it on your computer directly.

Labs are coding-focused assignments. There will be one roughly every week, released on Wednesday. Lab instructions are posted online. You will complete the lab by writing code in RStudio, then “rendering” the file to a pdf and submiting that on Gradescope.

Capstone Project

The whole point of this class is to give you powerful tools to answer questions, feed your curiosity, and solve real-world problems. In that vein, we want to let you work on topics that you care about.

The point of the project is to apply all of your current course learnings to some real data, on a topic that you care about.
Mid-semester we’ll post more details and talk to you about it in class.
You’ll work in teams of 2-3. You can pick your teammates or we can help you form groups.
You’ll choose a dataset from a list of pre-curated datasets provided by the instructors. There’s a wide range of topics, so find something that intrigues you.
To ensure that everyone stays on track, we’ll have several smaller deliverables leading up to the final submission. E.g. the first deliverable will be “who is your team?”

AI Policy

Instructors aren’t naive. We know that we can’t really stop students from using AI chatbots when doing their work, even if we wanted to.

So, you can use AI to get help in this course. However, 1) there are rules around it (below), and 2) it can really sabotage your learning if you’re not careful.

What we have seen in past semesters is that students will put a worksheet problem into ChatGPT, see the answer, think “that makes sense,” and copy it into their work. Then these same students fail on similar questions on quizzes. Why?

A finding from cognitive psychology is that recognizing a correct answer is much easier than producing it. Can’t think of the name of that familiar-sounding song on the radio? I bet if someone tells you what they think the name is, you’ll quickly know if they’re right or wrong. That’s so much easier than coming up with it from scratch.

And so it is with AI and this class. Most of your grade is quizzes and the final exam, where you will be asked to produce answers to questions. If you are used to having AI do your solving for you, with you just nodding along, then you’re going to be surprised on quizzes when you realize you can’t actually do the problems yourself.

So… no AI? Not exactly.

Tips for responsible AI use:

Embrace the struggle - To maximize your learning (and grade), try hard to solve problems without AI/googling first. This is another cognitive psychology finding: the act of struggling to remember something strengthens memory. Even if you eventually need to get help to solve the problem, you’ll understand and remember it much better if you struggled with it first.
Don’t just feed AI entire problems from your work. You’re setting yourself up for the surprise-bombing of quizzes described above. Instead, ask it to explain concepts. E.g. “when is a boxplot versus a violin plot more appropriate?”
It’s often subtly wrong in explanations of complicated things. It’s a fine idea to ask AI for a fresh explanation of something you’re struggling with, but you have to take it with a grain of salt. We have repeatedly seen AI explanations that sound great but are subtly wrong in important ways. These bots always speak confidently, eloquently, and sound so reasonable! But when the topic is complicated, they’re commonly just-a-little-off in a way that matters enormously. So, be responsible. Double-check anything it tells you against the notes/tutorials/work you’ve done in class, or check with an instructor or tutor.
AI’s great for things you rarely need to do. Want to do something funky, like put a math equation in the title of a plot? Or change the bars in a bar plot to be a stack of pigeons instead? Chatbots are great here - simple questions, simple answers.
Never copy/paste their output into your work. Use the AI to learn what you have to, then develop the solution yourself.

In other words: beware.

Group Work, Individual Submissions

Tables in most of our classrooms are set up so groups of 4-6 of you are seated around a table together. We expect people to work together to solve and understand problems. You can work with anyone in the room, or by yourself.

However, the work you turn in must represent your own understanding, not a copied answer. Each person turns in their own work on Gradescope - it is not a joint submission unless we say otherwise.

Labs are even stricter. Your submissions must contain only your individual work, not a copy of something you solved with a friend. You can discuss how to solve problems with a friend, or show them your code and ask for help, but you can’t just write the code once with someone else and submit separate copies. See below for clarifications

Even if you only care about grades, you are absolutely shooting yourself in the foot if you blindly copy from others. Worksheets/labs are each small parts of your grade, but quizzes (and the final) are not. And you’ll bomb the quizzes if you don’t actually understand the assignments you submit. We see it every semester.

The following examples of collaboration are allowed and in fact encouraged!

Discussing how to solve a problem with a classmate.
Showing your code to a classmate along with an error message or confusing output.
Posting snippets of your code to the discussion forum when seeking help.
Helping other students solve questions on the discussion with conceptual pointers or snippets of code that doesn’t whole hog give away the answer.
Googling the text of an error message.
Copying small snippets of code from answers on Stack Overflow.
Asking chatGPT or a similar tool for help with a coding error (not to get the solution to a problem), or help understanding concepts. Note that if the solution is wrong, you will lose credit.

The following examples are not allowed. In fact, many of the behaviors described below will hinder your learning experience, rather than enhance it:

Leaving a representation of your assignment (the text, a screenshot) where students (current and future) can access it. Examples of this include websites like course hero, on a group text chain, over discord/slack, or in a file passed on to future students.
Accessing and submitting solutions to assignments from other students distributed as above. This includes copying written answers from other students and slightly modifying the language to differentiate it.
Googling for complete problem solutions.
Posting questions into chatGPT or similar generative AI tools, and copying and pasting the output in your solution.

If you have questions about the boundaries of the policy, please ask.

Violations of policy

The integrity of our course depends on our ability to ensure that students do not violate the collaboration policy. We take this responsibility seriously and forward cases of academic misconduct to the Center for Student Conduct.

Students determined to have violated the academic misconduct policy by the Center for Student Conduct will receive a grade penalty in the course and a sanction from the university which is generally:

First violation: Non-Reportable Warning and educational intervention
Second violation: Suspension/Disciplinary Probation and educational interventions
Third violation: Dismissal.

And again, if you have questions about the boundaries of the collaboration policy, please ask!

Late Work

Reading Questions:

Each of these assignments is worth such a tiny part of your grade that we don’t give extensions for these. They don’t take much time at all, so please try to complete them on time.

Labs, Worksheets, and Projects:

Late submissions will be accepted with a penalty of 10% for each day past the deadline, up to a maximum of three days. Assignments more than three days late will not be accepted.

If you experience a serious emergency (for example, a visit to the ER) that prevents you from requesting an extension in advance, please reach out to your instructor. For extensions longer than three days (such as for long-term illness or emergencies), you’ll need to provide a DSP accommodation or speak with your instructor.

Getting help - office hours and group tutoring

See the “office hours” link at the top of the website for a schedule of instructor office hours and group tutoring sessions.

GROUP TUTORING IS GREAT

Almost every day of the week, there is a block of several hours where you can come to a classroom and have access to tutors to help you with your assignments. We strongly encourage you to simply take any unfinished work to group tutoring and do it there. You may have no questions (great!), but if you hit any snags, you’ll have help on the ready.

Side story: the best advice that I (Everett Wetchler - one of the instructors) ever received as an engineering undergraduate student at Duke was this: “start your homework during TA office hours.” I took this literally. I would go when office hours began, then sit and open the book to the homework problems for the first time. The TA was there if I got stuck. This was a HUGE win in my education.

Put differently – don’t feel like you need to bring specific question to group tutoring. You can certainly do that, but you can also just go do your work there, where help is ready if you need it.

Instructor office hours

Your instructors also hold office hours. You are welcome to come to them with questions about the course or anything else. Note that each instructor generally only has about 2 hours a week of office hours. Group tutoring is available for 10+ hours/week.

We ask that you try to only visit the office hours of your instructor, but you are welcome to visit any group tutoring session (not just the ones with tutors from your section). If you want to meet with an instructor who is not your own, please email them first to ask.

Other things to know

Rules of decency

Be a good human.
Discrimination/harassment based on race, gender, ethnicity, sexual orientation, or frankly anything else will not be tolerated.
Academic dishonesty will also not be tolerated. We will take any violations of academic integrity to the Center for Student Conduct, in addition to any grade penalties that ensue. Repeat violations will result in failure.
Berkeley Honor Code:
> As a member of the UC Berkeley community, I act with honesty, integrity, and respect for others.

Add/drop deadlines, PNP deadlines

See here and here. This is under the university’s control, but currently it says the add/drop deadline is “Wednesday, September 16 at 11:59 p.m.,” and the deadline to switch beetween a letter grade and pass/no-pass is “Friday of the 10th week of instruction,” which would be October 30, 2026.

Websites and tools used in this course

Course website: Your one-stop shop to get to everything you need for this course. Bookmark it! https://stat20.berkeley.edu/fall-2026/.
bCourses: Announcements will go out here, and sometimes we put class files on bCourses for you to access. This is usually things like datasets, extra notes, etc.

All of the tools below are linked to on this website – check out the little icons in the top right of the page.

RStudio: The computing platform you will use this semester. As a Berkeley student, you have your own version of RStudio waiting you for at: http://stat20.datahub.berkeley.edu. Most students taking Stat 20 have no experience programming; we’ll teach you everything you need to know!
DataHub: While RStudio is a program you could just run on your own computer, we have everyone use the link (above) to access a cloud-based version of RStudio. This means you don’t have to install anything on your computer, and it means that nothing will get lost even if your computer breaks during the semester.
Ed: The class discussion forum. Here you may ask questions about course content, or, via the private feature, message the instructors and staff about something personal. Please default to using the private Ed feature rather than e-mail if you wish to contact your instructor!
Gradescope: You will turn in ALL assignments here. We will be sending out an Ed post about how to format your submissions. Please read this as you will lose points if your work is incorrectly formatted. Gradescope is also the platform where your assignments will be graded, so you can return there to get feedback on your work. You are welcome to file a regrade request if you notice that we made an error in applying the rubric to your work. Note that regrade requests will need to be submitted by a deadline, which will usually be about three days after the grades are released.

Supplementary learning materials

The “textbook” for the course is the online notes and tutorials. We gradually release them as the semester goes along. Between those and class work, we’ll teach you everything you need to know!

If you’re looking for a supplementary textbook, here are (some of) the other resources we think you may find helpful. None of these are required.

Introduction to Modern Statistics by Çetinkaya-Rundel and Hardin (freely available online)
Statistics, Freedman, Pisani, and Purves
Data Visualization: A Practical Introduction, Healy (freely available online)
Hands-on Programming with R, Grolemund (freely available online)
R for Data Science, Wickham and Grolemund (freely available online)

Staying Well

Mental Health

If, at any point in the semester, you are feeling overwhelmed, stressed, anxious, depressed, or otherwise mentally unwell, UC Berkeley has excellent resources for you, available immediately. If you’ve never used these before, try a low-stakes drop-in call with a counselor at CAPS - Counseling And Psychological Services.

They can also help you find a longer-term talk therapist, psychiatrist, etc if you are in need.

If you have a mental health condition warranting academic accommodations, see DSP information below.

You can ALWAYS contact your instructor about anything you are going through. Berkeley is hard and we are here to shepherd you through it.

Disability accommodations (DSP)

UC Berkeley’s Disabled Students Program (DSP) is in charge of determining what, if any, special accommodations each student should receive based on their documented disabilities (including mental health diagnoses). They have drop-in hours and are generally quite available.

When formally granted, instructors receive documents directly from DSP and follow the instructions. These documents basically say, “Student X gets extra time for these things” or “Student Y may have disability-related absences that should be excused” etc. They never share any information about the nature of your disability.

The DSP program is generally for chronic or ongoing conditions. If you have a temporary circumstance – illness, family challenges, etc – that interferes with your coursework, contact your instructor as soon as you can. Any accommodations are at their discretion.

Campus Resources

If you ever need someone to talk to about anything that you’re going through, please feel to reach out to the instructors. For some topics, the tutors might be an even better resource because they are students just like you. Tutors can also tell you what being an Academic Student Employee (ASE) is like.

With regards to reports of sexual misconduct/violence/assault, you may speak with us as well, but know that we will need to report our discussion to the Title IX officer. This is detailed below.

As UC employees, the instructors (and tutors) are “Responsible Employees” and are therefore required to report incidents of sexual violence, sexual harassment, or other conduct prohibited by University policy to the Title IX officer. We cannot keep reports of sexual harassment or sexual violence confidential, but the Title IX officer will consider requests for confidentiality. Note that there are confidential resources available to you through UCB’s PATH to Care Center, which serves survivors of sexual violence and sexual harassment; call their 24/7 Care Line at 510-643-2005.

Below are some campus resources that may be helpful for you: