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DEPARTMENT OF STATISTICS AND DATA SCIENCE

Phd program, phd program overview.

The doctoral program in Statistics and Data Science is designed to provide students with comprehensive training in theory and methodology in statistics and data science, and their applications to problems in a wide range of fields. The program is flexible and may be arranged to reflect students' interests and career goals. Cross-disciplinary work is encouraged. The PhD program prepares students for careers as university teachers and researchers as well as research statisticians and data scientists in industry, government and the non-profit sector.

Requirements

Students are required to fulfill the Department requirements in addition to those specified by The Graduate School (TGS).

From the Graduate School’s webpage outlining the general requirements for a PhD :

In order to receive a doctoral degree, students must:

  • Complete all required coursework. .
  • Gain admittance to candidacy.
  • Submit a prospectus to be approved by a faculty committee.
  • Present a dissertation with original research. Review the Dissertation Publication page for more information.
  • Complete the necessary teaching requirement
  • Submit necessary forms to file for graduation
  • Complete degree requirements within the approved timeline

PhD degrees must be approved by the student's academic program. Consult with your program directly regarding specific degree requirements.

The Department requires that students in the Statistics and Data Science PhD program:

  • Meet the department minimum residency requirement of 2 years
  • STAT 344-0 Statistical Computing
  • STAT 350-0 Regression Analysis
  • STAT 353-0 Advanced Regression
  • STAT 415-0 I ntroduction to Machine Learning
  • STAT 420-1,2,3 Introduction to Statistical Theory and Methodology 1, 2, 3
  • STAT 430-1, 2 Probability for Statistical Inference 1, 2
  • STAT 440 Applied Stochastic Processes for Statistics
  • STAT 457-0 Applied Bayesian Inference

Students generally complete the required coursework during their first two years in the PhD program. *note that required courses changed in the 2021-22 academic year, previous required courses can be found at the end of this page.

  • Pass the Qualifying Exam. This comprehensive examination covers basic topics in statistics and data science and and is typically taken in fall quarter of the second year.

Pass the Prospectus presentation/examination and be admitted for PhD candidacy by the end of year 3 . The department requires that students must complete their Prospectus (proposal of dissertation topic) before the end of year 3, which is earlier than The Graduate School deadline of the end of year 4. The prospectus must be approved by a faculty committee comprised of a committee chair and a minimum of 2 other faculty members. Students usually first find an adviser through independent studies who will then typically serve as the committee chair. When necessary, exceptions may be made upon the approval of the committee chair and the director of graduate studies, to extend the due date of the prospectus exam until the end of year 4.

  • Successfully complete and defend a doctoral dissertation. After the prospectus is approved, students begin work on the doctoral dissertation, which must demonstrate an original contribution to a chosen area of specialization. A final examination (thesis defense) is given based on the dissertation. Students typically complete the PhD program in 5 years.
  • Attend all seminars in the department and participate in other research activities . In addition to these academic requirements, students are expected to participate in other research activities and attend all department seminars every year they are in the program.

Optional MS degree en route to PhD

Students admitted to the Statistics and Data Science PhD program can obtain an optional MS (Master of Science) degree en route to their PhD. The MS degree requires 12 courses: STAT 350-0 Regression Analysis, STAT 353 Advanced Regression, STAT 420-1,2,3 Introduction to Statistical Theory and Methodology 1, 2, 3, STAT 415-0 I ntroduction to Machine Learning , and at least 6 more courses approved by the department of which two must be 400 level STAT elective courses, no more than 3 can be approved non-STAT courses.

*Prior to 2021-2022, the course requirements for the PhD were:

  • STAT 351-0 Design and Analysis of Experiments
  • STAT 425 Sampling Theory and Applications
  • MATH 450-1,2 Probability 1, 2 or MATH 450-1 Probability 1 and IEMS 460-1,2 Stochastic Processes 1, 2
  • Six additional 300/400 graduate-level Statistics courses, at least two must be 400 -level

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