Ph.D. Program

The PhD program prepares students for research careers in theory and application of probability and statistics in academic and non-academic (e.g., industry, government) settings.  Students might elect to pursue either the general Statistics track of the program (the default), or one of the three specialized tracks that take advantage of UW’s interdisciplinary environment: Statistical Genetics (StatGen), Statistics in the Social Sciences (CSSS), and Machine Learning and Advanced Data Science (MLADS). 

Admission Requirements

For application requirements and procedures, please see the graduate programs applications page.

Recommended Preparation

The Department of Statistics at the University of Washington is committed to providing a world-class education in statistics. As such, having some mathematical background is necessary to complete our core courses. This background includes linear algebra at the level of UW’s MATH 318 or 340, advanced calculus at the level of MATH 327 and 328, and introductory probability at the level of MATH 394 and 395. Real analysis at the level of UW’s MATH 424, 425, and 426 is also helpful, though not required. Descriptions of these courses can be found in the UW Course Catalog. We also recognize that some exceptional candidates will lack the needed mathematical background but succeed in our program. Admission for such applicants will involve a collaborative curriculum design process with the Graduate Program Coordinator to allow them to make up the necessary courses. 

While not a requirement, prior background in computing and data analysis is advantageous for admission to our program. In particular, programming experience at the level of UW’s CSE 142 is expected.  Additionally, our coursework assumes familiarity with a high-level programming language such as R or Python. 

Graduation Requirements 

This is a summary of the department-specific graduation requirements. For additional details on the department-specific requirements, please consult the Ph.D. Student Handbook.  For previous versions of the Handbook, please contact the Graduate Student Advisor.  In addition, please see also the University-wide requirements at Instructions, Policies & Procedures for Graduate Students and UW Doctoral Degrees.  

General Statistics Track

  1. Core courses: Advanced statistical theory (STAT 581, STAT 582 and STAT 583), statistical methodology (STAT 570 and STAT 571), statistical computing (STAT 534), and measure theory (either STAT 559 or MATH 574-575-576).  
  2. Elective courses: A minimum of four approved 500-level classes that form a coherent set, as approved in writing by the Graduate Program Coordinator.  Each elective course must be worth at least 3 credits, and all elective courses need to be taken for a numerical grade. A list of elective courses that have already been pre-approved or pre-denied can be found here.
  3. M.S. Theory Exam: The syllabus of the exam is available here.
  4. Research Prelim Exam. Requires enrollment for and pass STAT 572. 
  5. Consulting.  Requires enrollment in STAT 599. 
  6. Applied Data Analysis Project.  Requires enrollment in 3 credits of STAT 597. 
  7. Statistics seminar participation: Students must attend the Statistics Department seminar and enroll in STAT 590 for at least 8 quarters. 
  8. Teaching requirement: All Ph.D. students must satisfactorily serve as a Teaching Assistant for at least one quarter. 
  9. General Exam. 
  10. Dissertation Credits.  A minimum of 27 credits of STAT 800, spread over at least three quarters. 
  11. Passage of the Dissertation Defense. 

Statistical Genetics (StatGen) Track

Students pursuing the Statistical Genetics (StatGen) Ph.D. track are required to take BIOST/STAT 550 and BIOST/STAT 551, and two other, numerically graded 500-level courses approved at the discretion of the Graduate Program Coordinator. Preapproved courses include STAT 516, STAT 517, GENOME 540, GENOME 541, and GENOME 562. These four courses may be counted as the four required Ph.D.-level electives. Additionally, students must complete at least three quarters of participation (one credit per quarter) in the Statistical Genetics Seminar (BIOST 581). This is a transcriptable program option, i.e., the fact that the student completed the requirements will be noted in their transcript.

Statistics in the Social Sciences (CSSS) Track

Students in the Statistics in the Social Sciences (CSSS) Ph.D. track are required to take four numerically graded 500-level courses, including at least two CSSS courses or STAT courses cross-listed with CSSS, and at most two discipline-specific social science courses that together form a coherent program of study. These courses may be counted as the four required Ph.D.-level electives. Additionally, students must complete at least three quarters of participation (one credit per quarter) in the CS&SS seminar (CSSS 590). This is not a transcriptable option, i.e., the fact that the student completed the requirements will not be noted in their transcript.

Machine Learning and Advanced Data Science (MLADS) Track

Students in the Machine Learning and Advanced Data Science (MLADS) Ph.D. track are required to take four numerically graded courses approved at the discretion of the Ph.D. Graduate Program Coordinator. Pre-approved courses include STAT 535, STAT 538, STAT 548/CSE 547, CSE 512, CSE 515, CSE 544 and EE 578. These four courses may be counted as part of the four required Ph.D.-level electives. This is not a transcriptable option, ie., the fact that the student completed the requirements will not be noted in their transcript.