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. Six of the seven 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 930, STAT 961, STAT 970 Spring: STAT 927, STAT 931, STAT 971, Summer: Qualifying Exam and First-Year Paper Year 2 Fall: STAT 972, Two Electives Spring: Three Electives Summer: Second-Year Paper
Year 3
Directed Reading & Research Admission to Candidacy Formulation of Research Topic	Fall: Independent Study Course, Two Electives, 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 900 and above, when offered.

 

The Program for the PhD Includes Seven Core Courses in the 2019-2020 Academic Year
STAT 927	Bayesian Statistics
STAT 930	Probability
STAT 931	Stochastic Processes
STAT 961	Statistical Methodology
STAT 970	Mathematical Statistics
STAT 971	Introduction to Linear Statistical Models
STAT 972	Advanced Topics in Mathematical Statistics

More advanced students choose from among various elective courses offered by the faculty of the Statistics 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.