The Center for Statistics and the Social Sciences was founded in 1999 with the triple mission of galvanizing collaborative research between social scientists and statisticians, developing a menu of new graduate courses for social science students, and enhancing undergraduate statistics training for the social sciences. Initiated with funding from the University Initiatives Fund, CSSS was the first center in the nation devoted to the interface of statistics and the social sciences. Adrian Raftery was the founding director of CSSS, and he served as the director for ten years. Raftery was followed by Thomas Richardson, who was the director from 2009 - 2014, Katherine Stovel from 2014-2017 and Darryl Holman from 2017 to 2022. Elena Erosheva is the current director of CSSS.
Since its founding in 1999, CSSS has developed into an established component of the University of Washington's research and training environment, with strong ties to the Statistics Department, multiple social science departments, and the University's eScience Institute. Currently four members of the UW faculty are designated as CSSS Core faculty members, while over 100 others are affiliated with CSSS.
Research
CSSS fosters research activities and collaborations in a variety of ways: through seminars, research funding, a consulting program, a working papers series, and the collaborative work of our core faculty. Our seminar meets weekly and is unusually interdisciplinary - both in terms of speakers and audience - and is often marked by a great deal of interaction and discussion.
Small research grants have been awarded to over 20 interdisciplinary projects featuring teams of investigators from Biostatistics, Demography, Economics, Linguistics, Political Science, Sociology, Statistics, and Microsoft Research. Several of these have already led to funded research grants from federal agencies.
Our Statistical Consulting for the Social Sciences assists social science researchers on campus and beyond. Over the past fifteen years, CSSS consultants have worked with hundreds of clients, including the State's HEC Board and United Way. Carlos Cinelli is currently the Director of Consulting; he is assisted by outstanding graduate student RAs.
Training
CSSS offers a rich menu of graduate courses in quantitative methods for social science students. These include loglinear modeling and logistic regression, applied regression, event history analysis, social network analysis, sample survey methods, Bayesian statistics for the social sciences, causal modeling, and visualization of data, as well as a review of mathematics for social scientists and an introduction to R.
Graduate students wishing to pursue advanced training in the statistics in the social sciences may complete a Ph.D. track through their home department or via our individualized track. These specializations typically involve successfully completing at least four graduate level CSSS courses and attending the CSSS seminar. Currently, tracks are available in Anthropology, Communication, Geography, International Students, Nursing, Political Science, Public Policy and Governance, Sociology, Social Work, Statistics, and Urban Design and Planning. The individualized track is an extremely popular option for students who are very interested in courses offered in CSSS but are not part of departments that have an established Ph.D. track.
We also offer a week-long Math Camp for graduate students every September. Math Camp provides the conceptual foundation, basic tools, and confidence necessary for students successfully undertake study of statistics in the social sciences.
At the undergraduate level, CS&SS offers two courses: STAT/CS&SS/SOC 221: Basic Statistics for the Social Sciences, and CS&SS 321: Data Science and Statistics for the Social Sciences I. CS&SS 221 is taught every quarter and provides an introduction to statistical reasoning for undergraduate social science students. CS&SS 321, taught in winter quarter, focuses on using programming to prepare, explore, analyze, and present data that arise in social science research.
