Prof. Judith Fan

Fall 2026

Project

By the end of this course, you will have completed an original research project! You will start from a quantitative claim about people — one you don’t quite believe, or one you are simply curious to check — find or collect real data that can speak to it, explore the data to discover patterns, and fit statistical models that describe those patterns. You’ll present what you found to your classmates at the course-wide project showcase.

Week 6: Milestone 5: A closer look at your data

This week your group will get its data ready and take a first close look at it. You will write a data dictionary for the variables in your two questions, make a histogram or bar graph of each variable on its own, and clean the data in R/prepare-data.R, which saves the result to data/processed/, along with three stopifnot() checks in R/checks.R. Then you will compute summary statistics, plot question 1, report what you have so far for question 2, and say which relationship you want to test in Milestone 6. You are encouraged to use an AI tool for the cleaning and plotting code; please write the descriptions of your plots and numbers in your own words. One submission per group, due on Gradescope by Sunday, November 1st at 11:59PM.

  • Milestone 5 handout (PDF): the steps and how it is graded. You will get a paper copy in section.
  • M5-closer-look.Rmd: the file your group fills in. Download it into the milestones/ folder of your group’s shared folder.

One member of the group should submit the .Rmd and the PDF it knits to on Gradescope (the link is on Canvas) and add the other members to the submission. Please bring your laptop to section.

Week 5: Milestone 4: Deciding on a research question

This week your group commits to its project. Start from the claims and datasets you wrote down in Milestone 3 and your TA’s comments, and choose one claim and one dataset; from now on, that pair is your group’s project. Then turn the claim into a question about how strong the relationship is between two variables in your data, naming the outcome and the explanatory variable. Suppose you find that relationship: write down at least three different data-generating processes that could have produced it, and for each one, what you would see in the data if it were the process at work. Look through your dataset’s documentation for other variables that could help you tell the processes apart, and pose a second question that builds on one of the alternative processes. AI tools can help you read the documentation and, once you have written your own list of processes, suggest more; write your own list first, and check any variable name an AI tool gives you against the str() output for your dataset. Show your TA your two questions before you leave section. Your group also receives a shared Google folder this week; the handout says how to set it up and who uploads the current files at the end of class. One submission per group, due on Gradescope by Sunday, October 25th at 11:59PM.

  • Milestone 4 handout (PDF): the steps and how it is graded. You will get a paper copy in section.
  • M4-questions-and-dgps.Rmd: the file your group fills in. Download it into the milestones/ folder of your group’s shared folder.

One member submits the .Rmd and the PDF it knits to on Gradescope (the link is on Canvas) and adds the other members to the submission. Please bring your laptop to section.

Week 4: Milestone 3: Your team and your data plan

This week you form your project group in section and start working together. From here on, the milestones are group work: one submission per group, and it is due on Gradescope by Sunday, October 18th at 11:59PM, although most groups will submit before they leave section. Groups are three students from the same section. In rare circumstances your TA may approve a group of two, but NO group may have more than three. For Milestone 3, you will fill out the team form, tell each other about your Milestone 2 claims and what you saw in your plots, and agree on how you will work together: how you’ll stay in touch, who submits, and who takes the lead on what. Then you’ll find the topics you have in common and write down at least one claim with a dataset that could test it. The member who will submit downloads that dataset so the whole group can look at it, and you write a data plan for it: the claim and a link to its source, a link to the dataset, who collected it and when, what you expect to find, and which columns you expect to use. AI tools are a good way to find datasets and to look up who collected one and when, but open the download page or the documentation yourselves before you write anything down. Please show your TA your plan before you leave section.

  • Milestone 3 handout (PDF): the steps and how it is graded. You will get a paper copy in section.
  • M3-team-and-plan.Rmd: the file your group fills in. Download it into the milestones/ folder of your project, next to your M1 and M2 files. Each of you can work in your own copy during section; the group submits one.

One member submits the .Rmd and the PDF it knits to (the Gradescope link is on Canvas) and adds the other members to the submission. Please bring your laptop to section, and be ready to say in a sentence or two what your Milestone 2 claim was and one question you still have about it.

Week 3: Milestone 2: Looking for patterns

This week you’ll start looking at your data. Every student makes an individual submission again, and it is due on Gradescope by Sunday, October 11th at 11:59PM. For Milestone 2, you will take the claim and the dataset from Milestone 1, make a histogram of one column yourself (no AI tools for that one), then use an AI tool to make the same histogram from a request in plain words and compare the two. Then you’ll decide which columns could test your claim, use an AI tool to make a plot of them, and write down what you see. This is the last milestone you do on your own: groups of three form in section next week.

  • Milestone 2 handout (PDF): the steps, an example, and how it is graded. You will get a paper copy in section.
  • M2-looking-for-patterns.Rmd: the file you fill in for this milestone. Download it into the milestones/ folder of your project, next to your M1 file. There is no new project folder to download; keep working in the one you made for Milestone 1.

Submit the .Rmd and the PDF it knits to (the Gradescope link is on Canvas). Please bring your laptop to section. Near the end of section, everyone will share the claim or topic they are working on, so start thinking about who you would like to work with.

Week 2: Milestone 1: Finding a claim and working in a project folder

You’ll be getting started on your final project this week. Every student will be making an individual submission, and it is due on Gradescope by Sunday, October 4th at 11:59PM. For Milestone 1, you will be setting up your project folder and finding a quantitative claim in the news, then tracking down a dataset you could analyze to check that claim against. You will learn how to load that dataset into an R Markdown notebook. You can use any AI tool you wish to help you accomplish these tasks.

  • Milestone 1 handout (PDF): the steps, a worked example, and how it is graded. You will get a paper copy in section.
  • Project template (zip): download it, unzip it into your psych10 folder, and rename the folder project-<your SUNet ID>. Inside are hello.Rmd, which you knit first to check that everything works, and milestones/M1-claim-and-setup.Rmd, the file you fill in for this milestone.

Submit the .Rmd and the PDF it knits to (the Gradescope link is on Canvas). Please bring your laptop, your claim, and the dataset you found to section this week, so your TA can help you get it loaded. Groups of three form in section next week, around related claims.

Week 1: Install Clinic

Your first discussion section is an R/RStudio install clinic where we will get R, RStudio, and the course packages running on your laptop, with your TA right there to help. Please bring a charged laptop! It will save time if you download the R and RStudio installers before section (the links are in the instructions).

This is not a numbered project milestone, so there is nothing to submit on Canvas. We WILL collect the first sheet of the instructions (pages 1-2) at the end of section, because that is how we track attendance that day. Pages 3-4 are yours to keep. It is preferred if you attend your scheduled discussion section, but you should feel free to attend any discussion section this week.

Final Project Showcase

The showcase takes place during the scheduled final exam time for this course: Wednesday, December 9, 3:30-6:30pm. Attendance is required for every group member. Room assignments will be announced in class and over Slack in advance.