The Princeton Sociology Summer Methods Camp gives incoming Sociology PhD students a running start at the beginning of their PhD program. The computational and statistical training provides necessary foundation for statistics and methods classes. We understand that participants come into the program with different backgrounds and experiences, and the Summer Methods Camp will be helpful for everyone, regardless of background.
This 2024 Summer Methods Camp will take place on 4 days: Tuesday, August 20; Wednesday, August 21; Thursday, August 22; Friday, August 23. Camp will run from 9am to 4pm in 165 Wallace Hall. Christina Pao and Varun Satish are this year’s graduate student instructors and Professor Brandon Stewart is the faculty advisor.
We have made code and slides used in the 2023 methods camp available on the Princeton Methods Camp GitHub page.
The Methods Camp is designed to give you training in both math and computing. In math, you will receive training in three main areas: calculus, probability, and matrix algebra. In computing, you will receive training in three main areas: data wrangling, iteration, and visualization.
At the end of the Methods Camp, students will be able to:
The only pre-arrival work required for this year is included in an email Christina and Varun sent to you on August 5th. Please email varun.satish@princeton.edu and christina.pao@princeton.edu.
Breakfast: 9:00 AM every day
Location: 165 Wallace Hall
Office hours: Christina and Varun will discuss options at the beginning of the camp.
Math: Calculus and its Applications
Morning session: 9:30 - 11:30 AM
Lunch session (with guest speakers): 12:00 - 1:30 PM
Afternoon session: 2:00 - 4:00 PM
Morning session: 9:30 - 11:30 AM
Lunch session (with guest speakers): 12:00 - 1:30 PM
Afternoon session: 2:00 - 4:00 PM
Morning session: 9:30 - 11:30 AM
Lunch session: 12:00 - 1:30 PM
Afternoon session: 2:00 - 4:00 PM
In day 4 we will be working on a mini-project with the Stanford Open Policing Project’s data (link).
Lunch session (with guest speakers): 12:00 - 1:30 PM
Should I participate in the camp if I have no plans to do quantitative work beyond what’s required? Yes! The aim of the camp is to make all students feel comfortable approaching the statistics training in the first year of the program, which in turn, is a crucial foundation for the second year empirical paper and future work. Both of us are available over email over the summer and will be holding daily office hours during the camp itself, and we’re both happy to spend extra time working with anyone more nervous about the quantitative requirements in the program to make sure you feel comfortable about the pace of the camp and related assignments.
Should I participate in the camp if I am highly confident about everything math and programming-related? Yes! Quantitative training means different things at different places, and the department wants to make sure everyone is on the same page going into the statistics sequence so that time isn’t spent during the course reviewing foundational concepts. In addition, the camp will feature lunchtime workshops highlighting qualitative methodology in the department, which is a good chance to meet professors you may not know already and get a sense of the range of the department’s work.
How does this camp fit into the first-year statistics sequence? The purpose of the camp is so that you can hit the ground running in whatever statistics sequence you opt to take your first year– both in terms of foundational math concepts and computing in R.
The Sociology Summer Methods Camp began in 2016, and the materials that we currently use include contributions from many of the people who have taught and participated in the program. Here is a list of all the instructors:
We would also like to acknowledge the many other people who have shaped the material including: the instructional staff of the Math Camp for the Department of Politics at Princeton and the instructional staff of the Math Camp for the Department of Government at Harvard.
All of the teaching materials that we created are available on GitHub. Please feel free to use and improve them.