PhD Program in Social Welfare

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Statistics Track

This document describes the guidelines for completing the Statistics Track in the Social Welfare PhD program and lays out general tips for those interested in pursuing the track.

Rationale

The Statistics Track in the Social Welfare PhD program enables students to develop advanced expertise and prepare to be educated readers and producers of Social Work research that builds on rigorous quantitative and statistical methodology. Planning a coherent personalized pathway early in the graduate career promotes effective use of statistical and quantitative skills in dissertation research and in professional life after the graduate school.

Description

The track is largely built around a curriculum developed by the Center for Statistics and the Social Sciences (CSSS). Students who complete the Statistics Track in Social Work acquire advanced training in statistics for social science research relevant to their own area of specialization. The CSSS provides a document certifying that the student completed the Statistics Track.

Statistics Track Committee

The Statistics Track Committee is composed of three members: the current instructor for Social Work Statistics sequence, a Social Welfare faculty member affiliated with CSSS, and a CSSS core faculty member. The Statistics Track Committee is responsible for approving students’ personalized pathway submissions and for keeping the Track description up to date. Policy changes in the track are discussed and approved by the PhD Steering Committee.

Track Requirements

Students complete four courses in social statistics with the grade of 3.3 or above in each course, and attend two quarters of the CSSS seminar, CS&SS 590.

Students select the four courses in social statistics from the list below; at least three courses should be CSSS 500-level courses. In addition, numerically graded advanced courses in Economics, Educational Psychology, Nursing, Political Science, Psychology, Public Health, Sociology, Statistics, and other departments may be considered as long as they help form a coherent set of social statistics courses.

These courses are in addition to the first three statistical methods courses required for the PhD in Social Welfare (two statistics, Soc Wl 587/588 or equivalent, plus one additional methods). The fourth required advanced methods course may be counted toward completion of the Track requirement. Completing a coherent set of advanced statistical methods courses prepares students to work at the cutting edge of statistics and the social sciences.

Interested students submit their proposal of four courses for approval by the Statistics Track Committee. The proposal also includes a statement describing the student’s rationale for the selection relative to their own research interests. Students pursuing approval of a pathway that includes a course not offered by CSSS and not included on the list of approved courses must provide the committee with a recent syllabus and a rationale for including the course in their plan.

Students are encouraged to seek advice from the Statistics Track Committee and their advisor in developing their personalized statistics pathway. A recommended time for the proposal submission is during the Fall quarter of the second year in the PhD program. Earlier submissions are encouraged.

Pathway changes may be made at any time by notifying the Committee and providing a rationale for the change. In most cases, changes that involve a listed approved course will be done automatically. Changes that involve a course not on the list will be considered similarly to a new proposal.

List of approved courses (joint course offerings are indicated in parentheses):
CS&SS 526 (SOC 529) Structural Equation Models for Social Sciences
CS&SS 529 (BIOST 529/STAT 529) Sample Survey Techniques
CS&SS 536 (SOC 536/STAT 536) Loglinear Models and Logistic Regression for the Social Sciences
CS&SS 544 Event History Analysis
CS&SS 560 (STAT 560) Hierarchical Modeling in the Social Sciences
CS&SS 564 (STAT 564) Bayesian Statistics for the Social Sciences
CS&SS 566 (STAT 566) Causal Modeling
CS&SS 567 (STAT 567) Statistical Analysis of Networks
CS&SS 568 Statistical Analysis of Game-Theoretic Data
CS&SS 589 (SOC WL 589) Multivariate Data Analysis for the Social Sciences
CS&SS 569 Visualizing Data
BIOSTAT 540 Analysis of Correlated Data
Numbers of the joint course offerings are indicated in parentheses. The Statistics Track Committee is responsible for periodically updating the list of approved courses.

Evaluation by the Statistics Track Committee

At the completion of two quarters of the CSSS seminar and all four courses, the student submits grades received in those courses to the Statistics Track Committee. The committee evaluates the performance in the course. A grade point average of 3.3 or above for the four approved courses is sufficient for a formal completion of the Statistics Track in Social Work. The committee may also give evaluations consistent with certifying the concentration, such as a pass with distinction. Finally, the committee may use its discretion to deal with grading in different departments that use different standards, or may request any papers written for the courses, for example, if the student is seeking approval of a credit/no credit class.

General Tips and Additional Information

Math Camp: http://www.csss.washington.edu/MathCamp/
The Math Camp is an intensive one-week introduction to fundamental concepts of mathematics and probability designed to help prepare social science graduate students for advanced courses in statistical methodology in general, and CSSS courses in particular. Math Camp is offered in September. Taking the Math Camp before the first year in the PhD program is recommended.

CSSS one-credit courses: Consider as preparation for more advanced courses.
CS&SS 505 Review of Mathematics for Social Scientists
CS&SS 508 Introduction to R for Social Scientists

Additional Training Opportunities

Summer program in quantitative methods of social research offered by the Inter-University Consortium for Political and Social Research (ICPSR), Ann Arbor, MI: http://www.icpsr.umich.edu/training/summer/index.html
Penn State’s summer institute on longitudinal methods, State College, PA: http://methcenter.psu.edu/summer/gallery.html
Look for specialized workshops in statistical methods that are often offered during or before major conferences (e.g., Joint Statistical Meetings or the annual conference of the Society of Social Work and Research).