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. If you are generally unable to attend class synchronously due to factors outside of your immediate control (e.g., different time zone), please tell us about these factors when completing the student background survey. Based on what we learn from you and your classmates from this survey, the teaching team will do our best to come up with reasonable accommodations so that you can still benefit from working with your classmates. 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

Digital access: Your experience in this course will be enhanced by having consistent access to a laptop/desktop with a wireless internet connection. If you do not have consistent access to a device that can connect to the internet, please fill out this form to request one from campus: https://eforms.ucsd.edu/view.php?id=490887. If you have other concerns related to digital access, please contact your TA via Slack.

Website: The primary website for the class is http://psyc60.github.io. We will use Canvas for in-class online quizzes, to submit assignments, and to post grades. We will use Slack to manage questions and online discussion.

Slack: Please post your questions about the course material and course logistics to Slack so that everyone can benefit from the answer. We also highly encourage you to answer your classmates’ questions whenever possible – you will get extra practice with the material and receive feedback from the teaching team about your answers. Members of the teaching team will generally aim to be responsive between 9am and 8pm. As an added incentive, students who provide frequent, high-quality answers may receive extra credit on their final course grades. If you have not yet joined the Slack workspace for this class, sign up by following this link. Remember to keep the guidelines about professional communication in mind.

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. The only communication channel that is officially supported in this class is Slack. If you email any member of the teaching team directly with questions about this course, or send a message in Canvas, you are not guaranteed to receive a reply.

Office Hours: If you need 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.

Tutoring: Peer tutors are available at the Teaching + Learning Commons in Geisel Library. Please find their schedule here. Note that there is no “Supplemental Instruction” (SI) support for this course.

Accommodations: Students requesting accommodations for this course due to a disability must provide a current Authorization for Accommodation (AFA) letter issued by the Office for Students with Disabilities (OSD) which is located in University Center 202 behind Center Hall. Students are required to present their AFA letters to instructors (please make arrangements to contact me privately) and to the Psychology Student Affairs Office.

What you will be doing

CourseKata Modules (40% of your grade)

Chapter sections will be assigned from “CourseKata Statistics and Data Science,” a free online and interactive textbook developed by Ji Son and James Stigler, together with their colleagues in the UCLA Teaching and Learning Lab.

• 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 sections prior to each lecture as listed in the schedule.
• We advise that you budget approximately 4-6 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 learn. However, your responses to these questions will be reviewed when determining your final CourseKata grade.
• Late Policy: If you are not quite done with your assigned CourseKata modules before class, 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 before the end of Week 10 (June 3, 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.

Final Project (28% 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. 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.
• 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.
• 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.

Labs (20% of your grade)

• There will be 5 Lab Assignments in this course.
• 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 and get to know your classmates.
• All parts of each lab must be submitted via DataHub by 11:59pm PT on the due date listed on the course schedule to receive full credit (e.g., All parts of Lab 1 are due by 11:59pm PT April 16).
• Lab assignments will be graded for completion and accuracy; however, demonstration of effort during class and attending your TA’s office hours may positively impact your lab grade, even when there are inaccuracies.
• 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; asking us to grade 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. 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 simply 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 — which is the actual point of being here!
• Honor Code: Unless otherwise stated, you can use any published 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!

Quizzes (10% of your grade)

• There will be 5 Practice Quizzes and 5 (Real) Quizzes in this course.
• All Quizzes and Practice Quizzes will be released on Thursday on Canvas at 5pm PT and must be completed by 4:59pm PT on Friday to earn full credit.
• 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 (non-Practice) Quizzes WILL count towards your final grade.
• Once you start a Quiz and Practice Quiz, you will have 30 minutes to complete it. You have two attempts at each quiz.
• 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-note but not “open-people” — meaning you can consult your own notes, but you should not consult with anyone when taking your quiz, should not try to “Google for” answers to the quiz questions, nor should you share your answers or provide any hints to anyone else.

SONA Study Participation (2% of your grade)

• Psychological science is based on observation and experimentation. Much of what we know about how people think comes from the participation of subjects in studies conducted at universities. During this quarter you will have the opportunity to see firsthand how research is done. Experiments range from 30 mins. to 2 hours, and are on a wide variety of topics. For example, some ongoing research looks at how people make decisions about what vacations to take, whereas other research looks at how the visual system allows us to detect moving objects. All research is safe and has been approved by the University’s human subjects review panel.
• The Psychology Department uses an online system called SONA to enroll in experiments and to assign credit. You can find everything you need to know about using the system on the Psychology Department webpage here for detailed information on how to get started.
• Follow this link to navigate to the UCSD SONA web portal.
• You are required to complete 3 SONA credit-hours to receive full credit for the SONA Study Participation portion of your grade.
• If you do not wish to participate in SONA, you can instead complete an alternative writing assignment. This will involve close reading of a contemporary primary research article in psychology and writing a thoughtful and constructive 3-5 page “review” of the article, as if you were involved in the peer-review process for that paper. It will be graded by the Instructor. All students who are opting to complete the alternative writing assignment should read the following paper:
  • Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349(6251). This
    • Here are some tips on how to write a “peer review” of a scientific paper.
    • Here is a worksheet to help you write an effective “peer review” of a scientific paper.

Grading

Grades will be determined as follows:

• CourseKata Modules (40%)
• Final project (28%)
• Lab assignments (20%)
• Quizzes (10%)
• SONA Study Participation (2%)

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. Consistent with the UC San Diego Principles of Community, 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 UC San Diego Office of the Ombuds.

Student Daily Feedback Survey

Throughout the quarter, please complete the linked daily feedback survey. The purpose of this survey is for the Instructor to better understand how things are going for you in this class, and to give you an opportunity to reflect on what you have been learning.

Note: If you complete more than 50% of the daily feedback surveys throughout the quarter, you will automatically earn 1% extra credit towards your final grade in this class. Please participate in the daily feedback surveys!

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.