Degree requirements

Course work

Candidates for the Doctor of Philosophy degree must satisfy all general requirements of the Graduate School. The following requirements must be met prior to the granting of the degree: 

  • Minimum of 72 graduate credits 
  • Minimum of 48 graduate credits of course work 
  • Minimum of 30 credits of 700-level graduate credits (not counting dissertation) • Minimum of 24 dissertation credits 
  • Maximum of 24 graduate credits (including a maximum of 18 700-level graduate credits) from a completed master’s degree program or previous post-baccalaureate work may be applied to the program, per Graduate Director approval 
  • All requirements, excluding prerequisite graduate courses, must be completed within 8 years immediately preceding the granting of the degree

Required courses

The following courses or their equivalents must be satisfactorily completed for the doctoral degree in
Statistics and Data Science:

  • MATH 713 – Abstract and Real Analysis (3 units)
  • STAT 705 – Probability Theory (3 units)
  • STAT 706 – Probability and Measure (3 units)
  • STAT 725 – Mathematical Statistics I (3 units)
  • STAT 726 – Mathematical Statistics II (3 units)
  • STAT 735 – Linear Models I (3 units)
  • STAT 736 – Linear Models II (3 units) (pending)
  • STAT 753 – Stochastic Models and Simulations (3 units)
  • STAT 755 – Multivariate Data Analysis (3 units)
  • STAT 756 – Survival Analysis (3 units)
  • STAT 758 – Time Series Analysis (3 units)
  • STAT 745 – Statistical Computing (3 units)
  • STAT 760 – Statistical Learning (3 units)
  • STAT 799 – Dissertation (minimum of 24 units)
  • Approved 600/700-level electives, based on research interests (9 units)

Electives

Electives will be approved by the student’s Graduate Advisory Committee. Appropriate courses outside
the Department of Mathematics and Statistics may be approved, depending on the student’s research
interests.
Example electives in Mathematics and Statistics Department:

  • STAT 653 Categorical Data Analysis
  • STAT 775 Advanced Topics in Statistics
  • MATH 630 Linear Algebra II
  • MATH 640 Topology
  • MATH 659 Topics in Probability
  • MATH 666 Numerical Methods I
  • MATH 667 Numerical Methods II
  • MATH 714 Real Analysis II
  • MATH 794 Research in Mathematical Sciences

Example electives in other programs:

  • ATMS 745 Atmospheric Turbulence
  • ATMS 746 Atmospheric modeling
  • BCH 706 Functional Genomics
  • BCH 707 Protein Structure and Function
  • BCH 709 Bioinformatics
  • BIOL 604 Population Genetics
  • CS 615 Parallel Computing
  • CS 657 Database Management Systems
  • CS 677 Analysis of Algorithms
  • EE 782 Random Signal Analysis and Estimation Theory
  • PHY 732 Statistical Mechanics

The department is in the process of developing other classes in Mathematics and Statistics that can be used as electives.

Qualifying exams

After the first year, and by the end of the third year, every student must pass one written qualifying exam in the theory of Mathematical Statistics (STAT 725 and STAT 726), and a written qualifying exam in one of the following areas: Qualifying Exam in Probability (STAT 705 and STAT 706) or Qualifying Exam in Applied Statistics (STAT 735 and STAT 736). The students will be allowed a maximum of two attempts at each of the exams in the first three years of the Ph.D. program. Each exam can be passed at the M.S. level (low pass) or Ph.D. level (high pass). To proceed with the Ph.D. program both exams must be passed at the Ph.D. level. If at least one exam is passed at the M.S. level, the student, if the academic record warrants it and the Graduate Committee approves of it, will end her/his program with an M.S. degree in Statistics and Data Science.

M.S. degree along the way to Ph.D

Students in the Ph.D. program in Statistics and Data Science may earn an M.S. degree in Mathematics with an emphasis in Statistics along the way to Ph.D., by satisfying the current M.S. degree requirements. Students qualify in the semester in which all degree requirements for the master's have been met. Students should apply to graduation using the paperwork required for an M.S. degree and a memo from the Statistics Graduate Program Director. A maximum of 24 credits (including a maximum of 18 700- level courses) used for the master’s degree can be applied to a Ph.D. degree, upon approval of the Program Director. The M.S. thesis credits used for an M.S. degree cannot be applied toward a Ph.D. degree. At the same time, the M.S. thesis credits can be counted as Ph.D. dissertation credits (upon Graduate Committee approval) if they have not been used for an M.S. degree. A maximum of 9 graduate credits earned outside of the program can be applied towards an M.S. Mathematics degree; these credits can be further applied to a Ph.D. degree as part of 24 credits transferred from M.S. to Ph.D. degree (in other words, up to 24 credits can be double-counted, and up to 9 credits can be triple-counted). PLEASE CHECK THE GRADUATE SCHOOL’S WEB SITE FOR CURRENT CREDIT TRANSFER POLICIES.

Admittance to candidacy

To be admitted into Ph.D. candidacy, after successfully completing the first 2-3 years of coursework and passing written qualifying exams, a student must pass an oral exam in the area of specialty. Students will be expected to complete their oral exam by the end of their third year. The exam is directed by the student's Graduate Advisory Committee. A student is expected to submit a written dissertation proposal to the Graduate Advisory Committee prior to exam. The purpose of the exam is two-fold, serving both as a subject-specific oral exam and defense of a dissertation proposal. It provides students an opportunity to formulate a clear plan for their dissertation research, and to strengthen their background following their written exams and in preparation for conducting their own dissertation research.

Ph.D. dissertation

A student will prepare a Ph.D. dissertation supervised by a graduate faculty member in the Mathematics and Statistics department and approved by the student's Graduate Advisory Committee, followed by a public oral presentation. The dissertation is then submitted for the Graduate School and institutional approval.

Graduate School Academic Requirements

All graduate students must maintain a cumulative graduate GPA of 3.0. If their GPA drops below
3.0 they are either placed on probation or dismissed. Undergraduate courses will not count towards
graduate GPA.

Probation: students whose cumulative graduate GPA is 0.1 to 0.6 points below that needed for a 3.0
GPA are put on probation. Students are placed on academic probation for one semester. If they fail
to raise their cumulative GPA to 3.0 by the end of one semester, they are dismissed from their
graduate program. Thesis, dissertation, S/U graded credits, and transfer credits have no impact on a
student’s GPA.

Dismissal: students whose cumulative graduate GPA is 0.7 or more grade points below that needed
for a 3.0 GPA are dismissed. Dismissed students are no longer in a graduate program but may take
graduate-level courses as a Grad Special. Students wishing to complete their degree must obtain
approval to take graduate-level courses, raise their graduate GPA to at least 3.0 and then re-apply to
a graduate program. Any courses taken to raise their GPA will be included in the graduate special/
transfer credit limitation (9 credits for master’s degrees).

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Please note: this represents the program handbook for the 2020-2021 academic year only. For an archived version of a previous year's handbook, or to obtain a hard copy of this current year's program handbook, please contact the program director.