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Contact the
Daniel J. Evans School of Public Affairs for
enrollment information.
RATIONALE
The main goals of the PhD concentration in statistics are to provide students with applied
quantitative and statistical skills in Public Policy and Management, and with tools for
carrying out quantitative research. The track 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 Statistics Concentration will have advanced training in statistics for
social science research relevant to their own research needs. Taking a coherent set of CSSS
courses will expose students to the cutting edge of statistics and the social sciences.
CERTIFICATION REQUIREMENTS
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).
The student will submit a list of the courses to the Ph.D. faculty program coordinator for approval.
These courses must be more advanced than any required for a Ph.D. degree in Public Policy and Management.
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:
- CS&SS 526
- Structural Equation Models for Social Sciencess
- CS&SS 527
- Survey Research Methods
- CS&SS 529
- Sample Survey Techniques
- CS&SS 536
- Loglinear Models and Logistic Regression for the Social Sciences
- CS&SS 544
- Event History Analysis
- CS&SS 560
- Hierarchical Modeling in the Social Sciences
- CS&SS 564
- Bayesian Statistics for the Social Sciences
- CS&SS 565
- Inequality: Current Trends and Explanations
- CS&SS 566
- Causal Modeling
- CS&SS 567
- Statistical Analysis of Networks
- CS&SS 568
- Statistical Analysis of Game-Theoretic Data
- CS&SS 589
- Multivariate Data Analysis for the Social Sciences
The Ph.D. faculty program coordinator will be responsible for periodically updating the list of approved
courses.
Minimum Grade Point-Average.
Students must obtain a minimum grade point average of 3.3 for their four
approved courses.
Evaluation by the Statistics Concentration Committee.
When a student has completed all four courses, the student will submit to the Ph.D. faculty program
coordinator a packet including grades received and any written papers completed for the courses. The
Ph.D. faculty program coordinator will evaluate the performance in the course. In most cases this will
be a pass (if the student has met the 3.3 grade point average, and the courses taken form a coherent set).
The Ph.D. faculty program coordinator can also give evaluations consistent with certifying the concentration,
such as a pass with distinction. Finally, the Ph.D. faculty program coordinator can use its discretion
to deal with grading in different departments that may use different standards.
The Center for Statistics and the Social Sciences will provide a document certifying that the student
completed the Concentration in Statistics.
ADDITIONAL INFORMATION
Information about CSSS:
http://www.csss.washington.edu/
Other CSSS-sponsored tracks:
http://www.csss.washington.edu/Courses/PhD/
Current CSSS course offerings:
http://www.csss.washington.edu/Courses/
CSSS course descriptions:
http://www.washington.edu/students/crscat/cs&ss.html
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