Ph.D. in Biostatistics

Program Overview

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 comprehensive curriculum that covers both theoretical and computational aspects of Biostatistics.

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Competencies

The Doctoral degree in Biostatistics degree is accredited by the Council on Education for Public Health (CEPH).

Upon completion of the Doctoral degree in Biostatistics, all graduates will be able to:

• Competencies:
  • Conduct original research on the theory and/or methodology of biostatistics
  • Apply innovative theory and/or methods to scientific problems
  • Apply appropriate advanced data analysis and management techniques to analyze epidemiologic data
  • Communicate research findings and conclusions (written and oral) in a clear and concise manner
  • Serve as an expert biostatistician on collaborative scientific teams

• Total required credits:  67 credits

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.

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, and (4) previous course work in statistics or biostatistics, such as linear regression, introductory mathematical statistics, or courses from survey sampling, multivariate analysis, or other advanced topics. We do enter students who do not meet all these requirements, but these students are expected to make up any deficiencies during their studies and should demonstrate exceptional potential in their application.

Ph.D. in Biostatistics Curriculum

The total requirements for the Ph.D. in Biostatistics are 67 credits. The credits must be completed as core, dissertation, and elective courses to meet the requirements. 

• Public Health Requirements (6 credits)
  • EPH 600 Introduction to the Science and Practice of Public Health (3 credits)
  • EPH 621 Fundamentals of Epidemiology (3 credits)

• Core Courses (37 credits)
  • BST 603 Introduction to Probability Theory and Its Applications (3 credits)
  • BST 610 Introduction to Statistical Collaboration (3 credits)
  • MTH 625 Introduction to Mathematical Statistics (3 credits)
  • BST 630 Longitudinal and Multilevel Data (3 credits)
  • BST 640 Modern Numerical Multivariate Methods (3 credits)
  • MTH 642 Statistical Analysis (3 credits)
  • BST 650 Topics in Biostatistical Research (1 credit x 4 semesters)
  • BST 665 Design and Analysis of Clinical Trials (3 credits)
  • BST 676 Introduction to Generalized Linear Models (3 credits)
  • BST 680 Advanced Statistical Theory (3 credits)
  • BST 690 Theory of Survival Analysis (3 credits)
  • BST 691 High Dimensional and Complex Data (3 credits)

• Dissertation (12 credits)
  • BST 830 Doctoral Dissertation (pre-candidacy) (1-12 credit hours)
  • BST 840 Doctoral Dissertation (Post-Candidacy) (1-12 credit hours)

• Electives (12 credits)

  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.

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