Doctoral Curriculum

This program is designed for students who desire academic research careers. The foundation is a sequence of courses in probability, mathematical statistics, linear models and statistical computing. The program also encourages study in a cognate area of application.

Up to four courses per semester may be counted toward the overall requirement of 13 courses. The six core courses are usually taken in the first year.

 

Sample Program Sequence
Years 1 and 2
Coursework Examination Research Papers Research Activities Completion of Other Requirements by Field	Year 1 Fall: STAT 9300, STAT 9610, STAT 9700 Spring: STAT 9270, STAT 9310, STAT 9710, Summer: Qualifying Exam and First-Year Paper Year 2 Fall: Three Electives Spring: Three Electives Summer: Second-Year Paper
Year 3
Directed Reading & Research Admission to Candidacy Formulation of Research Topic	Fall: Independent Study Course, One Elective, Oral Exam/Thesis Proposal Spring: Electives or Directed Study Units
Year 4
Continued Research Oral Examination Dissertation	Independent Study and Dissertation Research

Electives must include suitable courses numbered 9000 and above, when offered.

 

The Program for the PhD Includes Six Core Courses in the 2023-2024 Academic Year
STAT 9270	Bayesian Statistics
STAT 9300	Probability
STAT 9310	Stochastic Processes
STAT 9610	Statistical Methodology
STAT 9700	Mathematical Statistics
STAT 9710	Introduction to Linear Statistical Models

More advanced students choose from among various elective courses offered by the faculty of the Statistics and Data Science Department and other departments at the University. There is also considerable opportunity to take individually-structured reading courses with faculty in the department.

 

Student Involvement in the Department

In addition to formal coursework, the student is expected to participate in the informal intellectual life of the Department of Statistics and Data Science. This includes attendance at departmental colloquia, where visiting speakers describe current research, plus participation in informal seminars investigating current topics of interest in a non-course setting.