Capstone Project

Github Setup

To create a shared repository for this project (for you and your partners + me), each person should go to https://classroom.github.com/a/NUgayC7E. One person create the team with the name capstone-name1-name2-name3. Then the others can join that team.

Work Structure

Make a copy of this checklist to structure your work.

Final Project

For this final project, you should develop a research question and address it with methods for time series, longitudinal, or spatial data.

The analysis completed for mini-projects serve as starting points for the expected data analysis, but this project should involve more depth of thought about the data context and how it plays a role in the modeling and/or should involve a method that goes slightly beyond the covered materials.

Your goal is to communicate about your research question and the methods you use to answer that question. Your audience is a Stat 155 audience. For the final project, you’ll complete

  • A written communication (same format as mini projects)
    • Maximum 20 pages
    • Explain, justify, and interpret
    • Avoid printing R code and R output in the final written document but include it in the qmd file
    • Limit the number of visualizations (only include those important for your narrative)
    • Spend time making plots look nice and accessible [only include “ink” that conveys information]
  • A group presentation that summarizes your work
    • 10-15 minutes
    • Maximum 15 slides
    • Make sure there is equity in voices within group
    • Tell a story about the data and your models
    • Same principles as above (no code or output; nice visuals; explain, justify, and interpret)

Your written and oral communication should include the following:

  • An introduction the data context (who, what, where, why, when, how) and the data
  • An introduction to your research question and why it is important
  • A discussion and justification of your models that explains WHY you made your choices
  • A presentation of the results of your models
  • A discussion of your conclusions based on the results and the limitations to the conclusions you can make.