### Graduate Degree Programs

Additional information about graduate degrees in Statistics is available in K-State’s Graduate Catalog.

#### Requirements for an MS Degree in Statistics

Required Courses:

- STAT 713 Applied Linear Statistical Models (3 credits)
- STAT 720 Design of Experiments (3 credits)
- STAT 770 Theory of Statistics I (3 credits)
- STAT 771 Theory of Statistics II (3 credits)
- STAT 860 Linear Models I (3 credits)
- STAT 945 Problems in Statistical Consulting (at least one credit)

Options: Two master’s degree options are available.

- Report Option: The student must take 30 credit hours of course work, and write a report for 2 additional credit hours (STAT 898).
- Non-report Option: The student must take 36 hours of course work and pass a comprehensive exam approved by the supervisory committee.

The report option is strongly recommended for all students, especially those for whom the master’s degree will be the terminal degree. In either case, the course work must include the required courses listed above plus electives, which have been approved by the student’s major professor.

In addition, all master students are expected to have a background in mathematics at lease at the level of calculus, along with prior knowledge of matrix or linear algebra.

#### Requirements for a PhD Degree in Statistics

Students are required to have 90 semester hours of course work and research credit.

- Up to thirty hours from a master’s degree program may be applied toward the 90 hours.
- At least thirty hours must be research hours (STAT 999).
- The remaining hours include required courses (below) and electives to be approved by the student’s major professor.

Required Courses: All doctoral students are required to include the following courses in their programs of study.

- STAT 842 Probability for Statistical Inference (3 credits)
- STAT 843 Statistical Inference (3 credits)
- STAT 860 Linear Models I (3 credits)
- STAT 861 Linear Models II (3 credits)

and at least 8 credit hours of 900 level Statistics classes selected from

- STAT 903 Statistical Methods for Spatial Data (3credits)
- STAT 904 Resampling Methods (3 credits)
- STAT 905 High-Dimensional Data and Statistical Learning (3 credits)
- STAT 907 Bayesian Statistical Inference (3credits)
- STAT 940 Advanced Statistical Methods (3 credits)
- STAT 941 Advanced Statistical Inference (3 credits)
- STAT 950 Advanced Studies in Probability and Statistics (variable credits)

In addition, all doctoral students are expected to have a background in mathematics at least at the level of advanced calculus. Students who do not have this background upon entering the Ph.D. program may include Advanced Calculus I and II in their programs of study.

#### Ph.D Qualifying Exam

Students interested in pursuing the Ph.D. are required to first pass a departmental Qualifying Exam. Subsequently, students pursuing the Ph.D. must pass the doctoral preliminary examination (see below) in order to be approved for degree candidacy by the Graduate School.

The Qualifying Exam consists of material from courses covering applied statistics, mathematical statistics and linear models. The exam will be given once a year, in January. Students may take the exam as early as desired. However, a student with an M.S. in Statistics who starts Ph.D. course work in the department during the fall semester must take the exam no later than after their first three semesters in the program. A student with an M.S. in Statistics who starts Ph.D. course work in the department during the spring semester must take the exam no later than the January following their first four semesters in the program. Students admitted to pursue the Ph.D. but without the M.S. in Statistics should plan to take the exam no later than the January following their first five semesters in the program. Waivers of this requirement may be granted but only in exceptional cases. Further, students who fail to take the exam on schedule may lose funding.

As noted above, the exam will consist of three parts: mathematical statistics, linear models and applied statistics. Students taking the Ph.D. qualifier will be required to pass two of the three subject area exams. Students may take all three exams. The courses listed below, as based on the department's offerings as of fall 2012, are only intended to indicate the scope of the material covered. They are not required as prerequisite to taking the exam. Mathematical Statistics: Stat 842, 843; Linear Models: Stat 860, 861; Applied Statistics: Stat 720, 870. Students who fail the exam may be granted a second chance when the exam is given again, during the following January. However, a second opportunity is not automatic and approval of such is based upon recommendation by the faculty.

#### Preliminary Exam

The Ph.D. Preliminary Exam consists of two components: a dissertation proposal and a public seminar.

##### Dissertation Proposal

The doctoral preliminary examination will consist of a substantial thesis proposal. It will be judged on how well the candidate has located a problem, searched the literature, read relevant material, and sufficiently refined the problem so that the candidate has a reasonable chance of writing an acceptable dissertation. The proposal will be presented to the candidate's supervisory committee in written form, and to the department and the supervisory committee in a public seminar. A candidate may take the preliminary examination at most twice. If the candidate fails the preliminary examination a second time, he or she will be dismissed from the Statistics graduate program.

The candidate must provide a complete written copy of the proposal to each member of the candidate's supervisory committee two full weeks before the anticipated date of the public presentation. At the same time, the candidate must provide a short (less than one page) summary or abstract to all faculty in the Department of Statistics, and arrange for a seminar. The candidate will provide faculty not on the supervisory committee a copy of the complete proposal at their request.

##### Public Seminar

The candidate will present the public seminar at a date mutually agreed upon by the candidate, the candidate's supervisory committee, and the department head. The candidate must notify the Graduate School one month before the scheduled date. At the conclusion of the presentation, there will be a time for general questions from the audience. After the general questioning period, the general audience will be dismissed, and a second questioning period will begin with the candidate's supervisory committee and other interested Department of Statistics faculty members in attendance. The candidate should be prepared to answer questions that address specific points in the proposal, courses on the candidate's program of study, and general statistical knowledge.

At the conclusion of the second questioning period, the candidate will be asked to leave the room, and any Department of Statistics faculty members still in attendance may stay to advise the candidate's supervisory committee as to the candidate's ability to pursue Ph.D. work. After providing advice, those who are not members of the candidate's supervisory committee will be excused. The candidate's supervisory committee will then discuss and vote on the candidate's performance, with a three fourths majority of favorable votes needed to pass the preliminary exam.

Details regarding the evaluation of the preliminary exam may be found in the Department Handbook (PDF).

##### Timetable for Taking the Preliminary Exam

The preliminary examination must be taken within five semesters of passing the departmental qualifying examination. The semester in which the candidate passes the qualifying exam is counted as semester one, and summers do not count toward the time limit. After passing the qualifying examination, the candidate should start preparing for the preliminary examination as soon as the supervisory committee determines that the candidate is ready.