Skip to main content

Social Work

Contact the School of Social Work for enrollment information.

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.


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.


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 a coherent set of 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.

At least three of the four selected courses should be CSSS 500-level courses from the list below. 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 must be in addition to the two foundation statistics courses and the two methods courses required for the PhD in Social Welfare (SocWl 587/588 and SocWl 580/581 or equivalent in other departments). One of the two additional elective graduate courses in advanced research methods required for the PhD may be counted toward completion of the Track requirement, contingent on the approval of the Statistics Track Committee.

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 below): If a course appears closed when registering under the disciplinary code (e.g., SOC 529), try registering under the CSSS code. CSSS course instructors are generally open to providing an add code if a course has been filled.

CS&SS 510 (POL S 510)
Maximum Likelihood Methods for the Social Sciences
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)
Analysis of Categorical and Count Data
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 569
Visualizing Data
CS&SS 589 (SOC WL 589)
Multivariate Data Analysis for the Social Sciences

Numbers of the joint course offerings are indicated in parentheses. The Statistics Track Committee is responsible for periodically updating the list of approved courses.

Application Guidelines For SSW Statistics Track

  • Provide your name, year in the program, and the name of your faculty advisor.
  • List all the courses that you are proposing to take to meet the Statistics Track requirements. In addition, list the first four foundation courses (SOC WL 580, 581, 587, 588 or their equivalent in other departments) and elective graduate course(s) in advanced research methods required for the PhD in Social Welfare that you are not applying to fulfill the Track requirements. For courses not yet taken, identify the quarter/year in which you anticipate taking them, including the two quarters of the CSSS seminar.
  • Provide grades for all numerically graded courses (including SWL foundation) that you have already completed. If you have completed a course that is graded credit/no credit, and would like this course to count toward the Statistics Track requirement, please include an individual project paper or assignments for that course that can be reviewed by the committee.
  • Provide a one- or two-paragraph description of the kind of research questions and related methodologies that constitute the guiding perspective for your course selections. This statement provides a conceptual rationale that is expected to be consistent with your course selections.
  • Note that the Track requires at least three 500-level courses that are offered or cross-listed with CSSS. If you are requesting an exception to this policy, please provide a rationale for that exception. For any course not offered by CSSS and not included on the list of approved courses provide the committee with a recent syllabus.

If you have any questions, feel free to contact either the Doctoral Program Director or a member of the Statistics Track Committee. Copies of previously approved proposals are available from the Program Coordinator.

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
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: Strongly recommended 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:

Penn State's summer institute on longitudinal methods, State College, PA: 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).

Other useful links