Team Project & Final Presentation

Math and Coding Camp

Karl Ho

2026-08-14

Team Formation

  • Teams of four students
  • Each member from a different major or discipline
    • No two teammates may share a primary field
    • Interdisciplinary mix is the point: bring your own lens to a shared problem
  • Teams are formed on Day 1 of Math camp (Thursday) and stay fixed through the presentation

Project Timeline

Day Focus
Thursday–Friday Math camp — form teams, choose topic
Monday–Tuesday Coding camp — draft proposal, implement analysis in R
Wednesday Final presentations
  • Presentations will be in 8/19/2026 afternoon session

Rules of Engagement

  • Whole-team participation — every member contributes to the analysis, not just the slides
  • Elect a team coordinator
    • Runs meetings, tracks deadlines, is the point of contact with faculty
    • Coordinator is a facilitator, not the person who does the work
  • Final presentation: 6 minutes total
    • Time is evenly distributed among all four members
    • Every member speaks; hard stop at 6 minutes
  • Q&A follow; any member may field a question

Project Scope: The Proposal

Your proposal (and presentation) must cover three components.

1. Research design

  • A clear, answerable research question
  • Data source, unit of analysis, and key variables
  • Assumptions and limitations you are willing to state out loud

2. Methods

  • The model you fit — e.g. linear or logistic regression
  • Why that model suits the question and the data
  • How you evaluate fit and interpret coefficients

3. Visualization

  • At least one figure that carries an argument, not just decoration
  • Readable labels, units, and a caption that states the takeaway

AI Usage Disclosure

Using AI tools is permitted and encouraged — hiding it is not.

  • Include an AI disclosure slide in your final deck stating:
    • Which tools you used (ChatGPT, Claude, Copilot, etc.)
    • What you used them for — brainstorming, debugging, code generation, writing, interpretation
    • What you verified yourself and how
  • You are accountable for every line you present
    • Be prepared to explain any code or result on request
    • “The AI wrote it” is not an acceptable answer during Q&A
  • Undisclosed AI use is treated as an academic integrity issue