Concentration in Social Statistics
Department of Geography

This document describes the guidelines for completing a Social Statistics concentration as part of a Ph.D. in Geography.

Rationale

The Social Statistics concentration in the Geography PhD program enables students to develop expertise in applied statistical skills and tools for carrying out quantitative research. The concentration is largely built around a curriculum developed by the Center for Statistics and the Social Sciences (CSSS; course code: CS&SS). Students who complete the Social Statistics Concentration will have advanced training in statistics for social science research relevant to their own research needs. A Letter of Recognition is awarded by the CSSS to students who complete the concentration.

Social Statistics Concentration Committee in Geography

The Social Statistics Concentration Committee is composed of at least two faculty members, and chaired by a faculty member who is affiliated with CSSS. The Committee is responsible for approving the students' Concentration plan.

Concentration Requirements

Students must develop a concentration that consists of four courses in social statistics that are approved by the Social Statistics Concentration Committee. These courses must be more advanced than any required for a Ph.D. degree in Geography. The courses should be selected to form a coherent concentration in social statistics.

The advanced courses offered by CSSS qualify for the concentration. For example, CSSS currently offers courses in generalized linear models, hierarchical models, Bayesian methods, event history analysis, simulation methods, and analysis of network data. In addition, relevant courses in Statistics and Biostatistics, and methodology courses in departments like Economics, Political Science, and Sociology may be considered so long as they help form a coherent set of social statistics courses. Students are encouraged to seek advice from the committee in developing their concentration.

Numerically graded courses in other departments may be considered, with approval of the Social Statistics Concentration Committee, as long as they help form a coherent set of social statistics courses.

The four courses must be completed with grades of 3.3 or above. Additionally, two quarters of the CSSS seminar, CS&SS 590, are required.

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:

  • 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 for the Social Sciences
  • CS&SS 560 (STAT 560) Hierarchical Modeling for 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 Social 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

Evaluation by the Social Statistics Concentration Committee

After completing the course requirements, the student submits grades received in those courses to the Social Statistics Concentration 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 concentration. 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 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.

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

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