BUSN 5000 Project Guide
Introduction
The Project is a summative assignment in which you draw on key course concepts to learn about an empirical relationship and document what you learn. You will use R and R Markdown to conduct the analysis and report your findings, “knitting” the two together in a slide deck.
What the project is about
The project involves a nontrivial examination of an important persistent feature of the US labor market, namely the difference in average pay between women and men. You often hear this expressed in terms like: “Women earn 78 cents for every dollar a man earns.” Your project will use recent Current Population Survey (CPS) data to document, quantify, and attempt to explain the pay gap. In Part I of the course, we will be pointing you to background material to anchor your analysis, but for now you might start with the work of Claudia Goldin.
Why we assign it
We assign it for two reasons. First, there are workflow principles to establish. How should you organize project files and think about the data pipeline so that your analysis is reproducible? This question cannot be adequately addressed through standard homework assignments. You need the experience of carrying out a meaningful empirical analysis from data acquisition to a beautiful deliverable that communicates your findings. Second, there are facts about the labor market you should know. How and why does pay typically vary over a career for women and men? The project walks you through the basic steps to answer such questions using the official monthly source for labor market information.
How to use this guide
This guide is your one-stop shop for how to carry out the project. It covers:
- How to set up your computer for the project work
- How to complete the Pre-project Exercise and why we require it
- How to complete the Main Project
- How to complete the Progress Check and why we offer it
- How to submit your work to Gradescope
- How to recognize and correct common errors
When you view the guide on a computer, you will see a left pane that toggles the major sections and a right pane that helps you navigate within a section.
We recommend reading through the entire guide once before you start the project.
The deadline for submitting each project-related assignment is 11:59 PM on the due date. Late submissions will not be accepted.
- Pre-project Exercise due: Fri, Jun 12
- Optional Progress Check: Mon, Jul 6
- Main Project due: Thu, Jul 23
If you find a section that’s wrong, unclear, or out of date, reach out to the teaching team — see Getting help in the Common Errors chapter for how to contact us.
What about AI?
The truth is we can one-shot this project with Claude Code or ChatGPT’s Codex and produce a deliverable that collects all the points. We know this because we understand the workflow principles the project teaches you and we have the domain knowledge to verify the analysis output.
This is not to say we discourage AI use – quite the contrary. Rather, we recommend using AI as an expert partner whom you can interrogate about all aspects of the project, from code syntax and functions to interpretation of results. One-shot attempts bypass all the learning opportunities and, without the requisite domain knowledge, may miss the mark.
Exam accountability
However you produce your slide deck, there will be accountability for your project work and findings on Exam 2.