This document describes the guidelines for completing a Social Statistics concentration as part of a Ph.D. in Urban Design and Planning.
The main goals of the PhD track in statistics are to provide students with applied quantitative and statistical skills in Urban Design and Planning, particularly for carrying out quantitative research. The track is based on the curriculum developed by the Center for Statistics and the Social Sciences (CSSS; course code: CS&SS). Students who complete the Statistics Concentration will have advanced training in statistics for social science research relevant to their own research needs. The CSSS courses will provide students essential statistics skills to conduct quantitative research in the social sciences.
Students must ensure they have the required statistical and mathematical background necessary prior to taking courses that count toward the concentration. The CSSS Associate Director can assist in evaluating a student's preparation. Additionally course instructors can be consulted about any necessary background and preparation.
Coherent Set of Four Courses in Social Statistics
Students will take a set of four courses in social statistics (chosen primarily from the list below) and attend two quarters of the CSSS seminar, CS&SS 590 . The student will submit a list of the courses to the Ph.D. Program Director for approval. These courses must be more advanced than any required course for the Interdisciplinary Ph.D. program in Urban Design and Planning. These courses should be selected to form a coherent concentration in social statistics.
The advanced courses offered by CSSS will automatically qualify for the concentration. For example, CSSS currently offers courses in hierarchical models, Bayesian methods, event history analysis, analysis of social networks, survey research methods, and others. In addition, relevant courses in Public Affairs, Statistics, Biostatistics, Anthropology, 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 their advisor and the Ph.D. faculty program coordinator in developing their concentration.
Students pursuing approval of a course plan that includes a course not offered by CSSS and not included on the list of approved courses must provide the Ph.D. faculty program coordinator with recent syllabus and a rationale for including the course in their plan.
List of approved courses:
- BIOSTAT 555 Spatial Epidemiology
- CS&SS 526 (SOC 529) Structural Equation Models for Social Sciences
- CS&SS 527 Survey Research Methods
- 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 554 (STAT 554/SOC 534) Statistical Methods for Spatial Data
- CS&SS 560 (STAT 560) Hierarchical Modeling for the Social Sciences
- CS&SS 564 (STAT 564) Bayesian Statistics for the Social Sciences
- CS&SS 565 Inequality: Current Trends and Explanations
- 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 589 (SOC WL 589) Multivariate Data Analysis for the Social Sciences
The URBDP PhD Steering Committee will be responsible for periodically updating the list of approved courses in consultation with the CSSS Graduate Committee.
Criteria For Approval
Students must obtain a minimum grade point average of 3.3 for their four approved courses. The Center for Statistics and the Social Sciences will provide a document certifying that the student completed the Concentration in Statistics.