The Ph.D. program in statistics at Montana State University prepares students for academic, industrial, business, or government employment. 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. The exams are described below. The dissertation must be an original contribution to statistical science and must include new material worthy of publication. There is no departmental foreign language requirement for the Ph.D.

A Ph.D. student typically takes at least 24 credits of statistics in courses numbered 500 and higher and six credits of mathematics (MATH 547 & MATH 586). Additional course work in statistics and/or mathematics may be necessary, depending on the candidate's chosen area of specialization and background. For instance, 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. Also, it is expected that a Ph.D. student will take seminar or directed study courses (STAT 500 or STAT 570) in his/her area of specialty.

Each Ph.D. student will participate in the statistics consulting seminar. Through this participation, the student will gain important experience in practical problem solving, computational statistics and statistical report writing.

The Ph.D. qualifying exam is identical to the core course portion of the statistics 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 PhD 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 course work in the M.S. core has been completed. Two post-master's attempts to pass the qualifying exam are allowed.

The written comprehensive exam for the Ph.D. in Statistics consists of two, 4-hour sessions. One session emphasizes methods and the other emphasizes theory. The exam is given each August with the specific date determined by the department. Once the written comprehensive examination has been passed, the student must pass the oral comprehensive examination.

The written Ph.D. comprehensive examination covers material in the student's concentration areas and in the Ph.D. core. The Ph.D. core consists of the following material.

1. The M.S. core (STAT 501-502 and STAT 505-506)
2. STAT 532 (formerly 549) Bayesian Data Analysis
3. STAT 550 Advanced Mathematical Statistics (prerequisite: MATH 547)
4. MATH 586 Probability (prerequisite: MATH 547)

Each student must devise at least two areas of concentrated study that are separate from the PhD core. Each area should include an amount of material (and at an appropriate depth) equivalent to two or three graduate level statistics or mathematics courses. The concentration areas must be approved by the student's committee and must include, in total, an amount of material equivalent to at least 6 graduate level courses. An area could involve course material from outside the department. Some examples are the following:

1. Modeling (STAT 539 & 578),
2. Multivariate Statistics (STAT 537 & 538 or STAT 537, 538, & 539),
3. Design (STAT 526 & 578),
4. Real Analysis (MATH 547 & 548),
5. Time Series (STAT 534 & I&ME 558), and
6. Biostatistics/Generalized Linear Models (STAT 524 & STAT 539).

Each session of the written comprehensive examination is graded separately as pass or fail. A failed session may be repeated once. Note, the four-hour theory exam is not solely over probability (MATH 586) and mathematical statistics (STAT 532 and STAT 550). In large part, it is an exam over the mathematical and statistical theory associated with the concentrated study areas.