Princeton Sociology Summer Methods Camp 2025

The Princeton Sociology Summer Methods Camp gives incoming Sociology PhD students a running start at the beginning of their PhD program. The computational 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 2025 Summer Methods Camp will take place on 3 days: Saturday, August 30th; Friday, September 5th; Saturday, September 6th. Camp will run from 9:15am to 3pm in 165 Wallace Hall. Christina Pao and Sofia Avila are this year’s graduate student instructors and Professor Florencia Torche is the faculty advisor.

We have made the assignments and slides we will use available on the Princeton Methods Camp GitHub page.

Learning objectives

The Methods Camp is designed to give you training primarily in computing, though we will also be reviewing some basic statistics and probability concepts.

At the end of the Methods Camp, students will be able to:

  • Start the semester excited and ready to learn new methods
  • Combine the 5 dplyr verbs, join data sets, and convert between long and wide formats
  • Write for loops and other methods for walking through lists and repeating code.
  • Make simple graphs in ggplot2, write Markdown documents, and write basic equations in LaTeX
  • Learn how to access and understand built-in functions in R as well as write your own.
  • Perform matrix addition, subtraction, multiplication

Pre-arrival

Coding Assignment

The only pre-arrival work required for this year was the pre-assignment which you’ve now all submitted. If you have any other questions before your arrival, please email Sofia and Christina at sofiaavila@princeton.edu and christina.pao@princeton.edu.

Methods Camp 2025 Schedule

Location: 165 Wallace Hall

We will have lunch every day at 12pm. If you haven’t yet, make sure to submit your lunch ordering form.

Day 1: Saturday, August 30th

Morning session: 9:15 - 12:00 PM

  • Purpose of methods camp and SOC 500
  • Pre-assignment discussion
  • Objects in R, setting up badic R settings, project workflow/management in R
  • Intro to Tidyverse for data exploration and manipulation

Afternoon session: 1:00 - 2:00 PM

  • Recoding variables, logical structure, variable types
  • Matrices, vectors, data structures (long vs wide, dataframe vs tibble)
  • Basic matrix operations by hand and in R.

  • Group work: 2:00 PM - 3:00PM

Day 2: Friday, September 5th

Morning session: 9:15 - 12:00 PM

  • Reshaping, merging, and saving/exporting data,
  • Math equations in LaTeX
  • Formatting in Rmd and Qmd and settings for code chunks
  • For loops and while loops

Afternoon session: 1:00 - 2:00 PM

  • Intro to data visualization

  • Group work: 2:00 PM - 3:00PM

Day 3: Saturday, September 6th

Morning session: 9:15 - 12:00 PM

  • Functions and libraries
  • Lists and apply functions

Afternoon session: 1:00 - 2:00 PM

  • Sampling functions (normal and uniform).
  • Introduction to random variable, probability and cumulative density functions
  • Analytical vs empirical (simulation-based) solutions

  • Group work: 2:00 PM - 3:00PM

FAQs

  • 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.

About

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:

  • 2016: Rebecca Johnson, Janet Xu (graduate students instructors) and Brandon Stewart (faculty advisor).
  • 2017: Janet Xu, Xinyi Duan (graduate student instructors) and Matthew Salganik (faculty adviser).
  • 2018: Xinyi Duan, Katie Donnelly (graduate student instructors) and Brandon Stewart (faculty adviser).
  • 2019: Katie Donnelly, Liv Mann (graduate student instructors) and Matthew Salganik (faculty adviser).
  • 2020: Liv Mann, Joe Sageman (graduate student instructors) and Brandon Stewart (faculty adviser).
  • 2021: No camp offered
  • 2022: Joe Sageman, Angela Li (graduate student instructors) and Brandon Stewart (faculty adviser).
  • 2023: Angela Li, Varun Satish (graduate student instructors) and Matthew Salganik (faculty adviser).
  • 2024: Varun Satish, Christina Pao (graduate student instructors) and Brandon Stewart (faculty adviser).
  • 2025: Sofia Avila, Christina Pao (graduate student instructors) and Florencia Torche (faculty adviser).

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.