Syllabus

Stat 20: Introduction to Probability and Statistics

Instructors

Andrea Massari

Jeremy Eli Sanchez

Gaston Sanchez Trujillo

Everett Wetchler

Term

Spring 2026

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.

Course Culture

  • This course is designed to teach 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.

  • Discrimination/harassment based on race, gender, ethnicity, sexual orientation, or 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. There is more on this later on the syllabus.

  • Berkeley Honor Code:

    As a member of the UC Berkeley community, I act with honesty, integrity, and respect for others.

Websites to know

  • bCourses: Announcements will go out here.

  • Course website: All course materials, including readings and assignments, will be available at https://stat20.berkeley.edu/. Click on the link for our semester from there. You do not need to buy any materials for our course!

  • 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!

  • 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 your 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.

Mode of Instruction

This course is structured as a flipped class, meaning that you will first be encountering new concepts in statistics and data science outside of class. Class time is therefore dedicated to expanding on the work you’ve done outside of class by working through questions solo, in groups, and as a class. Attendance is mandatory; more on that in the Assignments section.

Before class

It is your responsibility to:

  • read through the course notes relating to the topic that will be covered the next day
  • work through the reading questions associated with those notes on Gradescope by 11:59 pm on the day before class.

During class on Tue/Wed and Thu/Fri

Class time (2 hrs) will be spent on a range of activities, but the most common will be concept questions (using Poll Everywhere) and working through components of your Problem Sets and Labs. Therefore, the most efficient way to complete your assignments is to be an active participant in class.

During class on Monday

On Mondays, class is shorter (1 hr), and we will have either:

  • Workshops: less-structured class dedicated to finishing up work on your assignments, or
  • Quizzes: see information on quizzes below.

Group tutoring

Tutors will offer group tutoring sessions several times each week. This is an opportunity to finish up any assignments that you’ve started in class or review any topics that are confusing for you. Each group tutoring session will be staffed by 2-4 tutors. You’re welcome to attend any session that works well for your schedule. Check the Office Hours page to see the group tutoring schedule.

Group tutoring is a great place to go to meet other students and collaborate on assignments with tutors on hand to help you get unstuck.

Instructor Office Hours

The instructors will offer office hours each week across a range of times. We ask that you try to only visit the office hours of your instructor, but you are welcome to visit the tutoring sessions of any tutors, not just the ones who work in your section. We may adjust the office hour and group tutoring sessions schedule throughout the semester as we understand student needs and preferences. Please check the Office Hours page to see the times of the various office hour/group tutoring sessions.

Office hours are an opportunity to chat one-on-one with your instructor. Please come to office hours! Coming to office hours does not send a signal that you are behind or need extra help. On the contrary, coming to office hours early and often tends to co-occur with success in the course. Instructors are happy to chat about the course material, statistics in general, careers in statistics, and whatever other statistics or data science topics are on your mind!

Don’t come to class if you’re sick!

Maintaining your health and that of the Berkeley community is of primary importance to course staff, so if you are feeling ill or have been exposed to illness, whether it’s COVID-19 or something else, please do not come to class. All of the materials used in class will be posted to the course website. You’re encouraged to reach out to fellow students to discuss the class materials or stop by group tutoring or office hours to chat with a tutor or the instructor.

Materials

The primary materials for the course are the lecture notes, which will be posted to the course website in advance of class. We’ll teach you everything you need to know!

The following textbooks are useful supplementary texts but there is no need to purchase them:

RStudio

The software that we’ll be using for our data analysis is the free and open-source language called R that we’ll be interacting with via software called RStudio. 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!

Assignments, Exams, and Grading

Assignment Type Percentage Count1 # Drops
Reading Questions 5% 26 4
Attendance 7% 27 4
Problem Sets 20% 15 2
Labs 10% 11 2
Quizzes 33% 9 2
Final Exam 25% 1 0
Total 100%

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

Reading Questions

Reading questions serve to check your understanding and engagement while going through the lecture notes prior to class. There will be a handful of questions per lecture note. These questions could be a mix of multiple choice, short answer, and coding questions. You will answer them directly on Gradescope. The reading questions will be due 11:59pm on the day before class.

Attendance

  • Attendance is a crucial piece of the flipped classroom model, and as such, it will be a part of your grade. We will track attendance on all class days besides Mondays (which will mostly be reserved for Quizzes) and the last day of class (a workday for students to catch up and receive help on their last assignments). Based on our calendar this semester, this means that there are 27 days where we are tracking attendance.

  • If you attend at least 23 out of the 27 days where we track attendance, you will receive 100% in the Attendance category.

  • If you attend less than 23 out of the 27 days where we track attendance, your percentage in the Attendance category will be the number of days you attended divided by 23.

Problem Sets

During class, we will give you a second engagement with the day’s material in the form of a paper problem set with practice problems (the first engagement is the reading questions).

  • These problems will run like traditional homework problems and drill the concepts in the reading notes rather than asking you to apply the concepts with a data set, like the lab does.

  • Problem sets are graded credit / no credit, where full credit is given if you earnestly engage with the assignments (that is, put in a good effort to complete the problems).

  • One Problem Set will consist of two in-class problem sets (the Tue/Wed and Thu/Fri problem sets) and will be due each Tuesday at 7am. The format of submission is a scanned PDF of your work.

  • Problem Sets (with the exception of Problem Set 0) may be completed individually or in groups of two.

Labs

  • Labs are long-form, accuracy-based assignments designed to apply the concepts from the lecture notes in the cause of doing an analysis of real data. This will involve both writing code and communicating your thoughts and findings in English.

  • We’ll be working through some problems from the labs in class, but you may have to complete them on your own outside of class time.

  • When a lab is assigned, it will be due the following Tuesday at 7am. Labs are to be submitted individually.

  • The format of submission is a PDF– specifically, a PDF generated by rendering Quarto Documents (.qmd files) to HTML and then exporting the HTML into a PDF. Don’t worry if you’re not familiar with the Quarto Document and this process as we will teach you about it! Again, please follow the formatting instructions we will send out so that you don’t unnecessarily lose points.

Quizzes

Quizzes are 40-minute, in-person examinations that cover all new material since the previous quiz. They are not cumulative, but new material is often built upon old material. The quizzes have a novel format which is detailed below.

There are no make-up quizzes. See the table above, but we drop everyone’s lowest few quiz scores to allow for the inevitable missed quiz or two. The class is too large and complex to offer make-ups, so we offer drops instead.

Individual Portion (25 minutes)

You will take the quiz on your own. When time is up, we will collect everyone’s individual quiz before handing out fresh, blank quizzes for the group portion (below).

Group Portion (15 minutes)

You will retake the quiz in a group of size 2 or 3. The group is of your choosing. The goal is for you to learn from each other’s mistakes.

How is your final quiz score calculated?

Your final quiz score is the average of your individual score and the score obtained by your group. Make sure to pick a group that you trust.

Cheatsheet

You are allowed to bring a one-sided sheet of paper with hand-written notes to the quiz. Standard size paper only (8.5” x 11”, or A4), with your name in the upper right-hand corner, which you will turn in along with your group quiz.

We will allow notes hand-written on a tablet and printed, provided they are not shrunk down. That is, you can’t make a giant sheet and then shrink it to tiny font to pack in more notes. That would be unfair to your fellow students.

Final Exam

The final exam will be held in person during finals week. The time and date is Thursday, May 14, 2026 from 7-10pm.

Grading Policies

General

  • A grade calculator for the course is here. Feel free to make a copy and put in your own grades! The calculator does not have drops, but you can feel free to alter the copied spreadsheet to add them.
  • 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).

Accomodations for students with disabilities

Stat 20 is a course that is designed to allow all students to succeed. If you have letters of accommodation from the Disabled Students’ Program, please share them with your instructor as soon as possible, and we will work out the necessary arrangements. This includes extensions on assignments and quiz accommondations.

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 and Problem Sets:

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 during office hours.

Drops

Reading Questions

We will drop your lowest 4 reading questions scores.

Attendance

There are 27 days where we track attendance. You can miss up to 4 and still get full credit.

Quizzes, Labs, and Problem Set packets

We will drop your lowest 2 scores.

Collaboration policy

You are encouraged to collaborate with your fellow students on problem sets and labs, but the work you turn in should reflect your own understanding and all of your collaborators must be cited. Reading questions, the final exam, and the individual component of quizzes must reflect only your work.

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 non-public materials (quizzes, exams, rubrics-any private class materials) from their class without the written permission of the instructor.

The general rule: you must not submit assignments that reflect the work of others unless they are credited appropriately.

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 you will need to cite this use, and 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.
  • Working on the reading questions or individual quizzes in collaboration with other people or resources. These assignments must reflect individual work.
  • Submitting work on an quiz or final that reflects consultation with outside resources or other people. These assessments must reflect individual work.

Note that you must complete the Labs using code that we have taught you in the course.

If you have questions about the boundaries of the policy, please ask. We’re always happy to clarify.

Violations of the collaboration 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: (i) First violation: Non-Reportable Warning and educational intervention, (ii) Second violation: Suspension/Disciplinary Probation and educational interventions, (iii) Third violation: Dismissal.

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

Frequently Asked Questions

  1. What should I do if I’m on the waitlist?

    Attend both lecture and section (remember, we are teaching it as one two hour class), and submit all assignments on time. Visit your instructor on the first day of class so you can be added to the course Ed and Gradescope.

  2. Are class sessions recorded?

    No. Class sessions feature a mix of group problem solving, activities, and discussion and don’t lend themselves to recording. The course notes are the main reference source for the course. Any materials used during the class session will be posted to the course website.

  3. Are time conflicts allowed?

Stat 20 does not allow students to enroll with time conflicts.

  1. What if I join the class late?

    If you join the class within the first two weeks, read the syllabus and lecture notes, take a look at Gradescope to get a sense of any assignments that may have already passed, and visit office hours to check that you’re up to date with things. The first two weeks of material are very important so you must be able to make up assignments.

    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.

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: