# Statistics Ph.D. Program

Program Guidelines

To earn a Ph.D. in Statistics, a student must pass the Ph.D. qualifying exam, pass the Ph.D. comprehensive exam, and write and defend a Ph.D. dissertation.

A Ph.D. student typically takes at least 30 credits of statistics in courses numbered 500 and higher. Credits from graduate courses taken from another department can be included in the Program of Study with the approval of the student's Ph.D. Graduate Committee. Additional course work in statistics and/or mathematics may be necessary, depending on the candidate's chosen area of specialization and background. For example, a Ph.D. student is expected to have completed all courses required for the M.S. degree in statistics and may need to make-up one or more of these courses if deficient.

Each Ph.D. student will participate in the Statistics Consulting Seminar (STAT 510) for a minimum of two semesters. Through this participation, the student will gain important experience in practical problem solving, computational statistics and statistical report writing.

## Ph.D. Statistics Qualifying Exam

The Ph.D. qualifying exam in Statistics is identical to the M.S. comprehensive exam except that the exam must be passed at the Ph.D. Level (i.e., Ph.D. pass). A student who earned an M.S. in Statistics from MSU need not take the Ph.D. qualifying exam if the M.S. comprehensive exam was passed at the Ph.D. level. Other students are expected to take the Ph.D. qualifying exam during their first post-master's semester at MSU or as soon as coursework in the M.S. core has been completed. Two post-master's attempts to pass the qualifying exam are allowed.

Ph.D. Statistics Comprehensive ExamThe written part of the Ph.D. comprehensive exam in Statistics is given each August with the specific dates determined by the student’s Ph.D. Committee. Once the written comprehensive examination has been passed, the student must pass the oral comprehensive examination. The student has 2 chances to pass each exam. The written part of the Ph.D. comprehensive will consist of several components. These will typically include:

- A general review/summary related to the proposed research area.
- Reading and critiquing at least one journal article related to the proposed research area.
- Performing a data analysis with a written summary. The data analysis will be related to coursework taken by the student.
- A component related to Bayesian statistics and/or other relevant coursework determined by the student's Ph.D. Graduate Committee.

The requirements associated with each component are flexible. That is, the Ph.D. Graduate Committee will determine the exact details of each component with the goal of assessing the student’s potential for performing independent research in the proposed research area. The student will be given several days to submit her/his written summaries.

## More Information

For more information, refer to The Department of Mathematics Graduate Handbook.

Updated on: 03/25/2015.