Statistics, PhD
Degree: Doctor of Philosophy (PhD)
Field of Study: Statistics
Program Overview
A student must satisfy all of the general requirements of the School of Graduate Studies as well as the more specific requirements of the department to earn a doctoral degree. Each graduate student is assigned an initial academic advisor upon matriculation. The academic advisor's primary responsibility is to help the student plan an appropriate and sufficiently broad program of coursework and study that will satisfy both the degree requirements and the special interests of the student. With the aid of the academic advisor, each student must present a study plan indicating how they intend to satisfy the requirements for a graduate degree. At the appropriate time, PhD students are also required to form a thesis advising committee, including a permanent research advisor, in order to draft a syllabus for and schedule an area exam.
The doctorate is conferred not merely upon completion of a stipulated course of study, but rather upon clear demonstration of scholarly attainment and capability of original research work in statistics.
In addition to the doctoral coursework, all PhD students must complete the following specific requirements:
Qualifying Exams
Each student will be required to take two written qualifying exams in theoretical statistics and applied statistical modeling. Syllabi for the exams are available to students. Exams will be offered twice a year, usually in January and May. Students may attempt each exam up to two times. Under normal circumstances, students are expected to have passed both exams by the end of their fifth semester. There are three ratings of the exam: (1) Pass at the PhD level; (2) Pass at the MS level; (3) Fail. Students who fail to pass at the PhD level after two attempts will be given the opportunity to obtain an MS degree provided the student passes both exams at the MS level.
Area Exam
Each student will be required to pass an oral area examination showing knowledge of the background and literature in the chosen area of specialization. The exam will be administered by the student’s advising committee, chaired by the research advisor. The exam should normally take place within one year after final passage of the qualifying examinations at the PhD level and at least one year before the defense takes place. A student may retake the area exam once.
A written syllabus, with a list of the papers for which the student will be responsible, should be prepared and agreed upon by the student and advising committee at least two months before the exam takes place, at which time a specific date and time for the exam should be decided. Both the syllabus and the scheduled date of the exam should then be reported to the graduate committee. The student is required to submit to the advising committee a written report on the predetermined research topic at least two weeks before the exam date. Once the syllabus and exam date have been reported to the graduate committee, the student will advance to PhD candidacy.
Yearly Progress Reports
After passing the area exam, students will present yearly progress reports to their advising committees, usually in April. These reports will consist of a written summary of progress delivered to the advising committee.
Dissertation, Expository Talk, and Defense
Students are required to produce a written dissertation and present an oral defense. The dissertation is expected to constitute an original contribution to statistical knowledge. It must be provided to the defense committee at least two weeks prior to the defense. Students are required to give a colloquium-level presentation of their thesis work, open to all students and faculty, followed by an oral defense of the thesis work to the defense committee. The committee consists of at least four faculty members, including the student’s research advisor and at least one outside faculty member.
Deadlines for the thesis defense and approval of the dissertation are determined by the School of Graduate Studies. It is the student’s responsibility to be aware of deadlines and make sure they are met.
PhD Policies
For PhD policies and procedures, please review the School of Graduate Studies section of the General Bulletin.
Petitions
Any exceptions to departmental regulations or requirements must have the formal approval of the department's graduate committee. Such exceptions are to be sought by a written petition, approved by the student’s advisory committee or research advisor, to the graduate committee.
Any exception to university rules and regulations must be approved by the dean of graduate studies. Such exceptions are to be sought by presenting a written petition to the graduate committee for departmental endorsement and approval prior to forwarding the petition to the dean.
Program Requirements
A student in the statistics program must demonstrate knowledge of the theoretical foundations of statistics and a wide range of statistical modeling and computational methodology. This includes taking qualifying examinations in the areas of theoretical statistics and applied statistical modeling, and taking certain courses in these areas, as specified below. Statistics PhD students must take 36 credit hours of approved courses with a grade average of B or better. For students entering with a master’s degree in a mathematical subject compatible with our program, as determined by the graduate committee, this requirement is reduced to 18 credit hours of approved courses.
Qualifying Examination
Students are required to take qualifying examinations in the areas of theoretical statistics and applied statistical modeling.
Area Examination
A doctoral student in the statistics program must take an oral area examination in their chosen area of specialization. The subjects for the area exam will be determined by the student and their advising committee.
Course Requirements
| Code | Title | Credit Hours |
|---|---|---|
| Required Courses: | ||
| STAT 445 | Theoretical Statistics I | 3 |
| STAT 446 | Theoretical Statistics II | 3 |
| STAT 425 | Data Analysis and Linear Regression Models | 3 |
| STAT 426 | Multivariate Analysis and Data Mining | 3 |
| STAT 455 | Linear Models | 3 |
| STAT 448 | Bayesian Theory with Applications | 3 |
| STAT 495 | Statistical Consulting and Collaboration | 3 |
| STAT 545 | Advanced Theory of Statistics I | 3 |
| Electives | 12 | |
| Total Credit Hours | 36 | |