Program for Quantitative and Analytical Political Science

Welcome to QAPS

The Program for Quantitative and Analytical Political Science (QAPS) was established in 2009 to support theoretical and quantitative research in political science and its dissemination. We support graduate students through QAPS fellowships, host post-doctoral research fellows, offer statistical and formal theory consulting, hold quantitative skills workshops, throw conferences, and organize the Quantitative Social Science colloquium


End of an Era
Dec. 16, 2019

After four and a half years at QAPS, Will Lowe is leaving the university to become Senior Research Scientist at the Hertie School of Governance in Berlin. This position at QAPS will not be refilled, so until further notice this means that:

There will be no more QAPS computational skills…
QAPS Workshop Change
April 15, 2019

This Wednesday's workshop will now be about cleaning, structuring, and visualizing data with R (not about R package construction, as previously advertised*).

It will take place in Fisher Hall, Room 200 starting at 10:30am on Wednesday, April 17th. 

More details can be found here:

QAPS workshop canceled
March 20, 2019

Reminder: This morning's QAPS workshop (April 3, 2019) has been canceled.

Future Events

No upcoming events found.

Previous Events

Colloquium: Erin Hartman
Fri, Apr 26, 2019, 12:00 pm12:00 pm

Erin Hartman
Department of Political Science, University of California Los Angeles

Co-author: Naoki Egami (Princeton and Harvard)

Corwin 127
Colloquium: Simine Vazire
Fri, Apr 19, 2019, 12:00 pm12:00 pm

Simine Vazire
Department of Psychology, University of California at Davis

The Credibility Revolution in Psychology

A fundamental part of the scientific enterprise is for each field to engage in critical self-examination to detect…

Corwin 127
Workshop: Cleaning, Structuring, and Visualizing Data in R
Wed, Apr 17, 2019, 10:30 am10:30 am

This workshop focuses on how to load, clean, and restructure your data into a form suitable for summarizing in graphs and tables, and ready for your final analyses. We will use functions from the 'tidyverse' R packages to realize the key preparation steps in any empirical data analysis: data import, variable cleaning and construction, wide-to…

Fisher 200