Academics : Ph.D. in Biostatistics

Ph.D. in Biostatistics

The Ph.D. in Biostatistics, offered through the Division of Biostatistics in the Department of Public Health Sciences at the Miller School of Medicine, provides a flexible curriculum to cover the basics.

Depending on their background, a student will follow either a Track A and Track B stream to completion of the Ph.D. All students will be required to take elective courses referred to as cognates which will be linked in a substantive way to the Ph.D. dissertation. See below for details.

Cognates

All students are required to take a minimum of four 3-credit graduate courses in specific topics referred to as cognates which will be related in a substantive way to the Ph.D. dissertation. Extra criteria requiring courses closely related to the student’s thesis work, or that a member in a subject matter discipline be on the student’s advisory committee, may apply in some cases. The cognate requirement will enable students to produce a biostatistically-sophisticated Ph.D. thesis and provide outstanding opportunities for graduates.

Track A: Students who meet prerequisite requirements

(1) A minimum of three semesters of calculus, including partial derivatives and techniques for solving multiple integrals, (2) One semester of linear algebra, (3) One semester of probability theory, (4) Four additional courses in statistics or biostatistics. The four courses are to include a general introduction, linear regression, introductory mathematical statistics and at least one more course (commonly drawn from survey sampling, multivariate, time series, nonparametrics, etc.), and (5) At least two additional courses in statistics, biostatistics or related fields.

Track B: Do not meet all prerequisite requirements

During the first year, students are expected to make up any deficiencies. This will be decided on a case-by-case basis by the graduate program director.

Courses

The following represents a typical course load and the order in which courses would be taken for a student in the Ph.D. program. Course descriptions can be found by clicking on the course or see here.


Fall Y1 Course Credits
MTH 624 Introduction to Probability Theory 3
MTH 642 Statistical Analysis 3
EPH 600 Introduction to Public Health 3
Total 9
Spring Y1 Course Credits
MTH 625 Introduction to Mathematical Statistics 3
EPH 621 Fundamentals of Epidemiology 3
BST 675 Generalized Linear Models 3
Total 9
Fall Y2 Course Credits
BST 640 Applied Modern Multivariate Analysis 3
BST 650 Topics in Biostatistics Research 1
BST 665 Advanced Clinical Trials 3
Elective 3
Total 10
Spring Y2 Course Credits
BST 630 Longitudinal Data 3
BST 650 Topics in Biostatistics Research 1
BST 680 Advanced Statistical Theory 3
Elective 3
Total 10
Fall Y3 Course Credits
BST 610 Advanced Consulting Practicum 3
BST 650 Topics in Biostatistics Research 1
BST 670 Bayesian Analysis: Concepts, Theory and Computing 3
BST 690 Advanced Survival Analysis 3
Total 10
Spring Y3 Course Credits
BST 650 Topics in Biostatistics Research 1
BST 695 High Dimensional and Complex Data 3
Elective 3
Total 7
Y4 and beyond Course Credits
BST 649 Advanced Independent Study 1-3
BST 730 Pre-candidacy dissertation credit 1-12

Examinations

A written diagnostic exam will be given at the end of the first year to ensure the student has made up deficiencies and is making adequate progress. The examination covers basic foundational material every graduate should have thoroughly assimilated. Students who perform poorly on the exam are required to demonstrate their mastery of the material in some other way, which is handled on a case-by-case basis.

A second oral and written exam will be administered at the end of the third year. Once a student passes the second exam, they will formally become a Ph.D. candidate.

Examples of Electives

The following are examples of electives (some of which students have taken in the past). This is not meant to be an exhaustive list but rather illustrates the scope of available electives.

Course Description Credits
CSC 548 BioInformatics Algorithms 3
ECO630 Advanced Econometrics 3
EPH 711 Cancer Epidemiology 3
EPH 740 Basic Pathology 3
HGG 630 Variation and Disease 2
HGG 640 Family Studies and Genetic Analysis 2
BST 649 Advanced Independent Study 1-3
BST 670 Bayesian Analysis: Concepts, Theory and Computing 3