Prof. Judith Fan

Fall 2024

Syllabus

Why take this course?

It is impossible to understand the modern world without an understanding of statistics. From public opinion polls to clinical trials in medicine to online systems that recommend purchases to us, statistics play a role in nearly every aspect of our lives. The goal of this course is to provide an understanding of essential concepts in statistics — how to construct models to explain variation in data — as well as the skills to apply these concepts to real data.

At the end of the course, students will possess:

  • Statistical literacy: The ability to dissect and understand statistical claims in scientific research and popular media

  • Statistical ability: The skills necessary to apply statistical analysis methods to real data

  • Statistical curiosity: The interest in further developing their statistical skills and knowledge, and the confidence in your ability to do so

What we offer

My priorities as an instructor are to:

  • Emphasize conceptual understanding over rote memorization. It is not important to memorize formulae. Instead, we will focus on helping you get in the habit of reflecting on what you have learned, how it connects to other concepts you’ve learned, and how to apply it in new contexts.

  • Reward deep thinking over simply getting the right answer. I believe everyone enrolled in our course can learn to think critically about numbers and statistics, and to enlist computers to help them do so. The grading of quizzes and labs will be generous in this course. The lion’s share of your grade will reward good-faith engagement with the material and participation in class.

  • Prioritize hands-on activities over listening to me talk. As long as there are lectures built into this course, I will do my best to prepare material that presents abstract concepts via concrete examples, and include interactive elements as much as I can.

  • Give you authentic experience with modern statistical tools. Statistics is a broad and evolving field, not a fixed set of tricks. We will engage with real data in all its messiness using real statistical tools that practicing scientists use. We won’t be able to cover every interesting topic in statistics, and we won’t settle for superficial familiarity with terms. Instead, we will work towards a deep understanding and ability to apply a set of core concepts to a broad range of scenarios.

  • Continually improve this course over time. I will do my best to handle unexpected issues fairly, and incorporate your feedback to make this course better. Please expect that this syllabus is subject to change, but we will only aim to make changes that we think will improve your learning experience.

What we expect from you

The teaching team is looking forward to making this an awesome, positive, and supportive learning experience for everyone. These are the expectations we have of all students enrolled in this course, and your core responsibilities as a student:

  • Show up. This means attending lectures, sections, and the final project showcase.

  • Try. This means engaging sincerely with the material, even when — especially when — it’s hard. This means doing your best to figure things out on your own (e.g., Googling it, or checking the syllabus) before going to someone else for help. This course WILL require a lot of hard work and persistence, so please budget your study time accordingly.

  • Ask for help when you need it. This means letting us know when you are stuck, even after trying to figure things out on your own and consulting with your peers on Slack. This means coming to office hours and being prepared to describe your question, what you have already done to answer it, and what you are looking for from us.

  • Be professional. This means being actively respectful, courteous, and thoughtful when communicating with one another in class, over Slack, and with members of the teaching team. This means proofreading your messages to all members of the teaching team, and ensuring that you have provided enough context for us to provide an informative response.

Attending lecture: Attendance is expected at all lectures to participate in collaborative lab assignments. Owing to the “flipped” format of this class, lectures/sections from this class will not be recorded.

Attending discussion section: Weekly attendance of your assigned discussion section is expected, so you can participate in collaborative work towards final-project milestones. If you are unable to attend your assigned section in a given week, you may attend a different section with permission from both section leaders. Requests to attend an alternate section should be made at least 24 hours in advance. Please consult with your TA about the best way to get caught up if you have to miss section.

How we are supporting you

Textbook: We will be using an interactive textbook entitled “CourseKata Statistics and Data Science.” It is already embedded in Canvas and accessible as “Modules” to work through at your own pace. This textbook is provided to you completely free of charge.

Website: We will be updating the course website throughout the term: http://psych10.github.io. Canvas: We will use Canvas for in-class online quizzes, to submit assignments, and to post grades.

Slack: The only digital communication channel that is officially supported in this course is Slack. Here are some instructions on how to join the Slack workspace for this course. You can access Slack using a browser, but downloading the Slack app to your desktop or mobile device gives you the option to receive notifications on those devices.

  • It is a good idea to review these tips regarding Slack etiquette, particularly the part about replying rather than creating a new post and asking questions in channel, rather than through direct message to me. These tips will help keep notifications to a manageable level.
  • If you reduce your notification level, it is still your responsibility to review these channels periodically and respond appropriately.
  • If you have a question that is either personal or specific to you (others in the class would not need the answer), please send a Direct Message to your TA and/or Dr. Fan via Slack.
  • Please note that email and Canvas messaging are not supported in this class.

Office Hours: Office hours are a terrific resource that you should take full advantage of during your time at Stanford. If you are looking for one-on-one help that goes beyond what you’re able to get on Slack, please go to your TA’s office hours, or another member of the teaching team’s office hours. Office hours are also a great way to simply get to know your TA or Instructor better. The members of your teaching team are also interested in getting to know you! The better they know you and your unique interests, the better they will be able to provide mentorship and support to you in this class and beyond.

Digital access: It is important to bring a laptop to every in-class session to enable participation in hands-on activities. Students without access to a laptop may contact the Lathrop Learning Hub which provides access to laptops for students. If you have other concerns related to digital access, please contact your TA via Slack.

Accommodations: Stanford is committed to providing equal educational opportunities for students with a disability. Students who require accommodations are a valued and essential part of the Stanford community and our class. If you require an accommodation, please register with the Office of Accessible Education (OAE). Professional staff will evaluate your needs, support appropriate and reasonable accommodations, and prepare an Academic Accommodation Letter for faculty. To get started, or to re-initiate services, please visit: https://oae.stanford.edu/. If you already have an Academic Accommodation Letter, we invite you to share your letter with us. Academic Accommodation Letters should be shared at the earliest possible opportunity so we can partner with you and OAE to identify any barriers to access and inclusion that might be encountered in your experience of this course.

What you will be doing

CourseKata Modules (35% of your grade)

Chapter sections will be assigned from “CourseKata Statistics and Data Science,” a FREE online and interactive textbook.

  • Unlike a traditional textbook, you will be asked questions throughout each chapter. To receive full credit for the CourseKata portion of your grade, you are responsible for making good-faith attempts to answer ALL of the questions embedded in the assigned chapter by the end of the week that they are assigned.
  • We advise that you budget approximately 6-8 hours per week working through these CourseKata chapters. This is a lot of time! Please plan your study schedule accordingly.
  • Your responses do not need to be correct to receive full credit – the purpose of working on the embedded questions/problems is to help you keep track of how well you understand the material.
  • Late Policy: If you are not quite done with your assigned CourseKata modules by the time they are due, do not panic! Please take as much time as you need to complete these modules and engage with the material at your own pace. It is way more important to us that you learn by working through these modules than that you finish by a particular time. So long as you complete any CourseKata module by Wednesday during Final Exam Week at 11:59PM PT, you will still be able to receive FULL credit for it. However, we strongly recommend that you keep up with the recommended schedule for working through the CourseKata modules so you can come prepared to work on the lab assignments in class.

Labs (30% of your grade)

  • There will be 5 lab assignments in this course.
  • Each lab assignment will be broken down into three components: A, B, and C. Each of these components will be released on different days, but all due at the same time at the end of the day posted on the course schedule.
  • Most of our synchronous “lecture” time will be spent working in small groups to work on lab assignments that allow you to practice the concepts and skills covered in the Coursekata modules assigned for that day.
  • Attending class synchronously will allow you to get the most out of these lab assignments, collaborate with your classmates, and ask questions of the teaching team.
  • All parts of each lab must be submitted through Gradescope via Canvas by 11:59pm PT on the due date listed on the course schedule to receive full credit.
  • Lab assignments will be graded for completion and accuracy.
  • Late Policy: There will be NO extensions for lab assignments. NO exceptions. The reason for this strict late policy is that the teaching team works very hard to provide individualized feedback on labs in a timely manner; grading late labs places an undue burden on the teaching team.
    • What we mean by late: If you miss a lab deadline but would like to have the opportunity to earn credit, submit the lab as soon as possible. Think of submitting late as taking a calculated risk: If you submit the lab before the teaching team begins grading your assignment, then your lab will be graded as normal. But if you submit the lab after the teaching team tries to grade your assignment, then your lab will be considered missing and there will be no opportunity to earn credit for this lab.
    • Tradeoffs: If the deadline is fast approaching and you are still working on the lab, you can choose to submit your partially completed lab to receive partial credit for the work you’ve already completed OR you can take your chances by taking more time to complete the lab, knowing that if the teaching team begins an attempt to grade your lab and it is missing, you will receive zero credit for the entire assignment.
    • But what about emergencies? We will drop your lowest lab grade (i.e., all three components of a single numbered Lab assignment). We understand that sometimes there are medical/family emergencies, religious conflicts, or other reasons why you may not be able to submit a lab assignment on time. Rather than requesting an extension, which we cannot grant (so please do not ask for one!), take a deep breath! At the end of the quarter, we will automatically drop everyone’s lowest lab grade. This means that even if you have an overwhelming couple of weeks and miss a lab deadline, that zero will NOT affect your final grade. We still recommend you work through the lab assignment anyway, and coming to our office hours with questions, so you can learn and get the most out of this class — at the end of the day, the point of being here!
  • Honor Code: Unless otherwise stated, you can use any resource you wish to complete the assignments (textbook, internet, etc). You should also feel free to discuss the assignments with your classmtes. However, you should not explicitly share answers with your fellow students in person or electronically unless instructed to do so by the instructors. Sharing answers by copying and pasting code from other students will be viewed as a violation of the Honor Code. Please know that it is extremely easy for the teaching team to detect when you’ve copied and pasted code that another person wrote!
  • Regrade Policy: Generally speaking, we discourage regrade requests for lab assignments. The only exception will be in the case of clerical errors (e.g., typos). If you believe there was a clerical error made on your lab assignment, please reach out directly to the Instructor (not a TA) with your request between 24-72 hours of receiving your graded assignment. The Instructor will determine if the regrade request will be granted. If your lab is regraded, the entire submission will be regraded from scratch, and the score on the regraded assignment will be final. In some cases, the regraded assignment might receive a lower score than originally granted (e.g., if new errors are discovered during the regrading process).

Final Project (20% of your grade)

  • There is no midterm or final examination for this class: the scheduled final exam time will be used for our Final Project Showcase. Attendance at the final project showcase is mandatory and will count toward the final project grade.
  • These will be group projects and your project group will be assigned at the beginning of Week 3.
  • You and your classmates will collaboratively design a survey which will be distributed to the entire class. In most cases, the anonymized responses to this survey data will provide the basis for your final project.
  • Final Project Milestones 0-4 will be graded for completion only. The purpose of them is to give your TA an opportunity to see where you are and provide you with personalized feedback to help you and your group stay on track. Final Project Milestones 5-6 (Report & Poster) will be graded for accuracy and all submissions must be received on time to receive full credit.
  • Each group is responsible for submitting a final report following a template that the teaching team will provide.
  • Each group is responsible for designing a scientific poster to communicate their results at the final project showcase and submitting an electronic copy of this poster as a PDF via Canvas.
  • Late Policy: Final Project Milestones 0-4 that are submitted late may still receive full credit, but it is not guaranteed and late submissions will not yield as useful and timely feedback from your TA. Final Project Milestones 5-6 (Report & Poster) will NOT be accepted late. NO exceptions. The reason for the strict deadlines for these final milestones is that the schedule for grading them is very tight at the end of the quarter, and late submissions place an undue burden on the teaching team. Please plan your group submissions accordingly.

Quizzes (10% of your grade)

  • There will be 5 Practice Quizzes and 5 (Real) Quizzes in this course.
  • Each Practice Quiz will give you a chance to demonstrate your understanding of the same material that will be covered on the subsequent (Real) Quiz. The (Real) Quiz will not cover material that goes beyond the Practice Quiz that preceded it.
  • Your score on the Practice Quizzes WILL NOT count towards your final grade. Your score on the (Real) Quizzes WILL count towards your final grade.
  • All Quizzes and Practice Quizzes will be posted to Canvas on Monday at 2:00PM PT and must be completed by 2:35PM PT to earn full credit.
  • Once you start a Quiz or Practice Quiz, you will have 30 minutes to complete it, but we do not expect most quizzes to require 30 minutes to complete.
  • Late Policy: There will be NO extensions for quizzes and no makeup quizzes. No exceptions. Please do not contact the teaching team to request an extension or makeup quiz. At the end of the quarter, we will automatically drop everyone’s lowest quiz score. That means that you can afford to either miss a quiz or for a quiz to not go so well, and it will NOT affect your final grade.
  • Honor code: All quizzes are “open-book” and “open-note” but NOT “open-people” — meaning you can consult the textbook and your own notes, but you should not consult with anyone else when taking your quiz. So it is okay to consult the CourseKata modules, but please do not use the wider internet (e.g., Google, ChatGPT, etc.) to search for answers when taking the quiz. Please also do not share your answers or provide any hints to anyone else.

Attendance (5% of your grade)

  • A straightforward way to enhance your academic experience (and boost your grade) is to show up for class & participate actively.
  • Half of your attendance grade will be based on attending lecture; the other half based on attending your assigned discussion section.
  • Lecture:
    • We will almost always include some kind of interactive activity during during lecture. Participating in these activities and submitting your work will ensure that you receive attendance credit for that class period.
    • You will earn FULL credit for attending lecture by submitting work for 14 class periods. (Note that there are 30 lectures throughout the quarter!)
  • Section:
    • Your TA will provide you with instructions in your discussion section for reporting that you were present for class.
    • You will earn FULL credit for attending section by submitting work for 5 class periods. (Note that there are 10 meetings of your discussion section throughout the quarter!)
  • Because these attendance expectations are already so modest, exceptions to the course-wide expectations for attendance will be extremely rare — even in the case of athletic travel, religious observances, OAE accommodations. For the same reason, we will not adjust the attendance policy for students joining the course late (e.g., just before the add/drop deadline). Ultimately, if for any reason you are unable to attend even 14 lectures or 5 sections, we cannot recommend that you enroll in this course for credit this quarter.
  • Regular attendance beyond the minimum required for full credit will provide you with an opportunity to earn extra credit. How much extra credit will be announced in class later in the quarter.

Extra credit opportunities

There will be two additional extra credit opportunities this quarter.

Mid-quarter survey: Please submit the mid-quarter survey by EOD on Wednesday 11/13 to become eligible for one additional dropped quiz.

“Test your knowledge” activity: We will be setting aside time in lecture on Wednesday, 11/20 for an activity that allows you to demonstrate what you have learned so far this quarter. Participation in this in-person activity will make you eligible for one additional dropped lab assignment (in addition to the one dropped lab that everyone receives). There is no way to make up this activity, so if you want to participate you will need to come to lecture in person to do so.

Grading

Grades will be determined as follows:

  • CourseKata modules (35%)
  • Labs (30%)
  • Final project (20%)
  • Quizzes (10%)
  • Attendance (5%)

Grading scale. The grading scale will be as follows:

  • 97-100: A+
  • 93-96: A
  • 90-92: A-
  • 87-89: B+

and so on (rounding to the nearest whole number). We may curve up at the bottom of the scale depending on the distribution, but I will not curve down (i.e. 87 will never be worse than B+).

What We Expect From Everyone

Values we share: We are genuinely committed to equality, diversity, and inclusion in this course. We aim to provide an intellectual environment that is at once welcoming, nurturing and challenging, and that respects the full spectrum of human diversity in race, ethnicity, gender identity, age, socioeconomic status, national origin, sexual orientation, disability, and religion. We sincerely hope that you will share our commitment to actively creating and maintaining a safe environment founded on mutual respect and support. To be clear, this course affirms people of all gender expressions and gender identities. If you prefer to be called a different name than what is indicated on the class roster, please let us know. Feel free to correct us on your preferred gender pronoun. If you have any questions or concerns, please do not hesitate to contact any member of the teaching team.

Code of conduct: You are expected to treat the teaching team and your fellow students with courtesy and respect. This class should be a harassment-free learning experience for everyone regardless of gender, gender identity and expression, sexual orientation, disability, physical appearance, body size, race, age or religion. Harassment of any form will not be tolerated. For clear violations of course expectations for professional and respectful conduct in this course, whether in class or online, we may deduct points from the Attendance portion of a student’s grade, with the number of points proportional to the severity of the violation. If someone makes you or anyone else feel unsafe or unwelcome, please report it as soon as possible to a member of the teaching team. If you are not comfortable approaching the teaching team, you may also contact the Stanford Office of the Ombuds.

Course Privacy Statement: As noted in the university’s recording and broadcasting courses policy, students may not audio or video record class meetings without permission from the instructor (and guest speakers, when applicable). If the instructor grants permission or if the teaching team posts videos themselves, students may keep recordings only for personal use and may not post recordings on the Internet, or otherwise distribute them. These policies protect the privacy rights of instructors and students, and the intellectual property and other rights of the university. Students who need lectures recorded for the purposes of an academic accommodation should contact the Office of Accessible Education.

Affordability: Stanford University and its instructors are committed to ensuring that all courses are financially accessible to all students. If you are an undergraduate who needs assistance with the costs related to this class, you are welcome to approach me directly. If you would prefer not to approach me directly, please note that you can ask the Diversity & First-Gen Office for assistance by completing their questionnaire on course textbooks & supplies, or by contacting Joseph Brown, the Associate Director of the Diversity and First-Gen Office (jlbrown@stanford.edu; Old Union Room 207). Dr. Brown is available to connect you with resources and support while ensuring your privacy.

Students with Documented Disabilities: Students who may need an academic accommodation based on the impact of a disability must initiate the request with the Office of Accessible Education (OAE). Professional staff will evaluate the request with required documentation, recommend reasonable accommodations, and prepare an Accommodation Letter for faculty dated in the current quarter in which the request is being made. Students should contact the OAE as soon as possible since timely notice is needed to coordinate accommodations. The OAE is located at 563 Salvatierra Walk (phone: 723-1066, URL: http://studentaffairs.stanford.edu/oae).

Support services: During your time at Stanford, you may experience a variety of challenges that can cause barriers to learning, such as strained relationships, increased anxiety, alcohol/drug problems, feeling down, difficulty concentrating and/or lack of motivation. These mental health concerns or stressful events may lead to diminished academic performance or reduce your ability to participate in daily life. Stanford is committed to advancing the mental health and well-being of its students. If you or someone you know is feeling overwhelmed, depressed, and/or in need of support, services are available. You can learn more about the broad range of confidential mental health services available on campus here https://vaden.stanford.edu/caps-and-wellness/counseling-and-psychological-services-caps.

Student Background Survey

During Week 1, please set aside 20 minutes to complete the student background survey in one sitting. The purpose of this survey is for the teaching team to get to know you, how you think about learning, and relevant aspects of your circumstances that may affect your learning experience in this course.

Mid-Quarter Survey

Please set aside 15 minutes to complete our mid-quarter survey. Completion of this survey will make you eligible for one additional dropped quiz.

Acknowledgements

Many thanks to Prof. Ji Son, Prof. James Stigler, everyone in the UCLA Teaching and Learning Lab, Prof. Russ Poldrack and Prof. Tobias Gerstenberg for generously sharing their instructional materials.