Program Description
The PhD in Statistics and Data Science offers comprehensive learning in both theoretical and methodological aspects of statistics and data science, with a focus on applying these principles to diverse real-world problems. The program is multi-disciplinary in nature and includes coursework that spans the areas of statistics, machine learning, operations research, and computational mathematics. Graduates of the PhD program are well prepared for careers as university faculty and researchers, as well as for roles as research statisticians and data scientists in industry, government, and the non-profit sector.
Summary of Degree Requirements
Overview
Students admitted to this program must complete the MS in Statistics and Data Science en route, regardless of prior education. Beyond the MS requirements, there are four requirements in the PhD program: preliminary exams, coursework (see below), comprehensive exam, and dissertation. Details of these requirements are outlined below.
Preliminary Exams
Preliminary exams, also called the “prelim exams” or simply the “prelims,” comprise the first half of the university’s candidacy examination. The second half is the comprehensive exam. As such, students must pass the prelims before attempting the comprehensive exam.
Preliminary Exams are graded Pass/Fail. Graduate students in this track are required to pass the preliminary exams in both statistics and applied statistics. Students are given two attempts to pass these exams. The first attempt is in August after their first year, at which point students must attempt both exams. Students who do not complete the preliminary exam requirement on their first attempt are given a second attempt in January of their second year, and need only take the exam(s) they failed on the first attempt. MS students are allowed to take prelims and each pass and fail counts towards their progress. Any prelims taken by a graduate student become part of their permanent prelim record.
Listed below are the Prelim examination areas and the preparatory coursework for each. These courses are required, and students are strongly encouraged to take these courses before attempting the preliminary exams.
Statistics: MATH 8000 , MATH 8040
Applied Statistics: MATH 8050 , MATH 8850
Comprehensive Oral Examinations
Within one year of completing the preliminary examinations, a PhD student must complete a comprehensive oral examination (sometimes called the “third” or “fourth” exam). This exam comprises the second half of the university’s candidacy examination. The first half is the prelim exams. As such, students may only attempt the comprehensive exam after passing the prelims. The comprehensive exam is administered by the student’s dissertation committee. This oral examination is designed to demonstrate the student’s readiness to begin their doctoral research. Upon successfully passing the comprehensive exam, the student advances to candidacy for the PhD degree.
Dissertation
The final requirement of the PhD degree is the doctoral dissertation. PhD students are required to write a dissertation detailing their original and significant contributions to the body of research in their area of concentration and defend it.
Coursework
Coursework must include at least 24 hours of non-research, non-professional development graduate courses at the 8000 level or above. Courses taken in order to fulfill another degree may not be counted towards the degree. Courses taken outside of the core requirement (see below) should be selected from the following MATH 8020, 8060, 8070, 8080, 8090, 9010, and 9020. Exceptions to this policy may be granted in special circumstances by the Advisor and Associate Director for Graduate Studies. Coursework must also include at least 18 hours of MATH 9910 .
Core Requirement
The PhD core requirements consist of the courses listsed below. Note that students earn the MS degree en route to the PhD. It is strongly recommended that students take these courses according to the schedule outlined below. Any deviation from this schedule should be approved of by the Associate Director for Graduate Studies and the student’s advisor.
First Semester Fall:
Second Semester Spring:
Third Semester Fall:
Fourth Semester Spring:
Fifth Semester Fall:
Sixth Semester Spring:
Seventh Semester Fall:
Eighth Semester Spring:
Ninth Semester Fall:
Tenth Semester Spring:
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