Projects


Project 1: Designing and Analyzing a Random Sample

In this project, you will investigate a research question that can be answered by taking a random sample from a well-defined population and analyzing one variable from the collected data using methods we have learned.

Here are some examples of projects that past students have done:

  • Does the frequency of the letter Z on Wikipedia exceed its frequency in the English language? [report]
  • Are there fewer Subarus at Stanford than nationwide?
  • On average, is Trader Joe's cheaper than Safeway?
  • Are more than 90% of recipes in a vegetarian cookbook are actually vegetarian?

You are required to work with one partner for this project.

Data Collection: Both you and your partner should collect the data. Be sure to take lots of photos to include in your report and your poster. If you work in a research lab that collects data, I encourage you to see if any of the data from your lab would be appropriate for this project.

Report: You will analyze the data that you collected using techniques in the class and prepare one report with your partner. You will submit a draft, for which you should write up the Data Analysis without collaborating with AI or any human other than your partner. Then, you will submit a final draft, for which you are encouraged to use AI to check your work and polish your writing. However, you should only use terminology, formulas, and notation taught in this class. Any reports that use terminology, formulas, notation, or code not taught in this class will earn an automatic grade of 0 for both you and your partner. (Exception: You may use AI to generate code to help with making plots.)

Here is a template with instructions for the report.

Submission: You and your partner should join an empty Project 1 group on Canvas. Upload a draft by Wednesday, October 29 by noon to Canvas. Upload the final version by Wednesday, November 5 by noon to Canvas.


Project 2: Designing and Analyzing a Randomized Experiment

In this project, you will investigate a research question that can be answered by randomly assigning units to one of two groups and comparing the two groups using the methods we have learned. Here are some examples of projects that past students have done:

  • Does waxing skis increase speed? [report]
  • Does soaking popcorn kernels in water first reduce number of duds?
  • Does a high-carb meal before an athletic event improve performance?
  • Is recall affected by whether or not you take notes on a computer or by hand?

You are required to work with one partner for this project, who cannot be the partner that you worked with on Project 1.

Data Collection: As you collect the data, be sure to take lots of photos to include in your report and your poster. You will need to submit your data with your project. I recommend using Google Sheets and downloading the file as CSV.

Report: You will analyze the data that you collected using techniques in the class and prepare one report with your partner. You will submit a draft, for which you should write up the Data Analysis without collaborating with AI or any human other than your partner. Then, you will submit a final draft, for which you are encouraged to use AI to check your work and polish your writing. However, you should only use terminology, formulas, notation, and code taught in this class. Any reports that use terminology, formulas, notation, or code not taught in this class will earn an automatic grade of 0 for both you and your partner. (Exception: You may use AI to generate code to help with making plots.)

Here is a template with instructions for the report.

Submission: You and your partner should join an empty Project 2 group on Canvas. Upload your data (as a CSV file) to Canvas and a draft by Friday, November 21 by noon to Canvas. (However, everyone has an automatic one week extension if you need it.) Upload the final version by Friday, December 5 by noon to Canvas.


Poster Presentation

Instead of a final exam, you will turn one of your projects into a poster and present it at one of two poster sessions:

  • Friday, December 5 from 1:30 - 3 PM (i.e., class time) in the Sequoia Courtyard (weather permitting)
  • Wednesday, December 10 from 3:30 - 6:30 PM in CoDa E160.

You are encouraged to present the poster with your project partner, if possible. Join a group on Canvas with your partner, corresponding to the date that you want to present. If you want to present at the early session on 12/5, you must join a group by Wednesday, December 3 at noon (even if you are presenting solo).

Your poster will need to be printed on 24" x 36" paper. You may select all the most basic printing options (e.g., matte paper, no lamination, not mounted). There are a few options for printing:

  • For students presenting at the normal session on 12/10: if you upload a 24" x 36" PDF of your poster to Canvas before Monday, December 8 at 5 PM, we will print the poster for you and bring it to the Wednesday poster session. This is the only free option and is only available to people presenting on Wednesday. If you are late, then you must arrange your own printing.
  • Copy Factory at 3929 El Camino Real: $29.46 with Stanford discount (use coupon code STANFORD at checkout)
  • FedEx at 249 California Ave: $34.05 with Stanford discount (e-mail poster to usa5101@fedex.com and place order in person, showing your student ID)
  • Staples at 700 Menlo Park: $36.05
  • Tech Desk on campus: $50 plus tax
You should allow for at least 2 days turnaround time. Please let us know if we can help with pick-up.

Here is a poster template that you can use, although you are welcome to use your own. (This is adapted from a template made by Nic Fishman.)

Don't forget to upload a PDF of your poster to Canvas, even if we are not printing the posters for you.

You will be graded on the quality of your poster and presentation skills. The majority of the grade will be shared between you and your partner (if you have one), but there will also be an individual grade for how well you individually answered questions about your project. Finally, you will be required to peer review 4 other posters during the poster session (when you are not presenting). Click here to see which session you are presenting in.