Overview

The PhD 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.

Admitted PhD students are expected to take a full suite of courses including several iterations of the seminar course, a consulting practicum, and a series of elective coursework (cognate area) that ensure the candidate has studied a subject matter discipline within biomedical research. PhD students are also expected to take high-level courses in statistical theory, survival analysis, and high-dimensional and complex data not generally taken by MS students. The PhD program consists of 37 credits of core coursework, 6 credits of introductory public health coursework, 12 credits of electives, and 12 credits of dissertation research for a total of 67 credits to complete the degree.  PhD students are expected to pass a first-year written diagnostic exam at the end of their first year of study.  A second oral and written exam will be administered at the end of the third year. 

To obtain additional information on the PhD in Biostatistics, please visit our Graduate Programs in Public Health website.

Admission Requirements

  • All applicants for the PhD in Biostatistics program must submit the following items on SOPHAS
    • Application fee
    • Curriculum Vitae/Resume
    • Three letters of recommendation
    • Statement of Purpose/Personal Statement
    • Official transcripts from every post-secondary school attended
    • Graduate Record Exam (GRE)
  • This graduate degree program also requires submission of certain supplemental materials, including:
    • TOEFL/IELTS score, as applicable
    • Foreign evaluation on international transcripts, as applicable

For more detailed information, please visit our Public Health Sciences Graduate Studies Admission Website.

For further information, please contact:

Ginelle Solis, EdD, MPA
Director of Admissions and Recruitment
Department of Public Health Sciences
University of Miami Miller School of Medicine
Tel: 305-243-7246
Email: publichealthadmissions@miami.edu 

Curriculum Requirements

Core Courses
BST 603An Introduction to Probability Theory and Its Applications3
MTH 625Introduction to Mathematical Statistics3
MTH 642Statistical Analysis3
EPH 600Introduction to the Science Practice of Public Health3
BST 610Introduction to Statistical Collaboration3
EPH 621Fundamentals of Epidemiology3
BST 630Longitudinal and Multilevel Data3
BST 640Modern Numerical Multivariate Methods3
BST 650Topics in Biostatistical Research 14
BST 665Design and Analysis of Clinical Trials3
BST 676Introduction to Generalized Linear Models3
BST 680Advanced Statistical Theory3
BST 690Theory of Survival Analysis3
BST 691High Dimensional and Complex Data3
Electives12
Dissertation12
Doctoral Dissertation (pre-candidacy)
Doctoral Dissertation (Post-Candidacy)
Total Credit Hours67

1 BST 650 is taken for 1 credit in Fall and Spring during the first 2 years of study

Sample Plan of Study

Admitted PhD students are expected to take a full suite of courses including several iterations of the seminar course, a consulting practicum (or advanced computing course), and a series of elective coursework (cognate area) that ensure the candidate has studied a subject matter discipline within biomedical research. PhD students are also expected to take high-level courses in statistical theory, survival analysis, and high-dimensional and complex data not generally taken by MS students.

The PhD in Biostatistics program consists of 37 credits of core coursework, 6 credits of introductory public health coursework, 12 credits of electives, and 12 credits of dissertation research for a total of 67 credits to complete the degree.  Students complete structured coursework (core and elective credits) during the first three years of study.  PhD students are expected to pass a first-year written diagnostic exam at the end of their first year of study.  A second oral and written exam will be administered at the end of the third year of study.   

This is a sample plan of study.  Your actual course sequence may vary depending on your previous academic experience as well as current course offerings.  Students should meet with their academic advisor each semester to determine appropriate course selection.

Plan of Study Grid
Year One
FallCredit Hours
BST 603 An Introduction to Probability Theory and Its Applications 3
EPH 600 Introduction to the Science Practice of Public Health 3
MTH 642 Statistical Analysis 3
 Credit Hours9
Spring
MTH 625 Introduction to Mathematical Statistics 3
BST 630 Longitudinal and Multilevel Data 3
BST 676 Introduction to Generalized Linear Models 3
 Credit Hours9
Summer
BST 610 Introduction to Statistical Collaboration 3
 Credit Hours3
Year Two
Fall
BST 665 Design and Analysis of Clinical Trials 3
BST 650 Topics in Biostatistical Research 1
BST 640 Modern Numerical Multivariate Methods 3
Elective Coursework 3
 Credit Hours10
Spring
BST 650 Topics in Biostatistical Research 1
BST 691 High Dimensional and Complex Data 3
BST 680 Advanced Statistical Theory 3
Elective Cousrework 3
 Credit Hours10
Summer
BST 830 Doctoral Dissertation (pre-candidacy) 1
 Credit Hours1
Year Three
Fall
EPH 621 Fundamentals of Epidemiology 3
Elective Coursework 3
Elective Coursework 3
BST 650 Topics in Biostatistical Research 1
 Credit Hours10
Spring
BST 690 Theory of Survival Analysis 3
BST 650 Topics in Biostatistical Research 1
BST 830 Doctoral Dissertation (pre-candidacy) 1
 Credit Hours5
Year Four
Fall
BST 830 Doctoral Dissertation (pre-candidacy) 1
 Credit Hours1
Spring
BST 830 Doctoral Dissertation (pre-candidacy) 3
 Credit Hours3
Year Five
Fall
BST 840 Doctoral Dissertation (Post-Candidacy) 3
 Credit Hours3
Spring
BST 840 Doctoral Dissertation (Post-Candidacy) 3
 Credit Hours3
 Total Credit Hours67

Mission

The Doctorate Program in Biostatistics prepares students who have demonstrated excellence in mathematics, statistics, and the natural or social sciences to become research biostatisticians in academia, industry, or government positions, with a general focus on biostatistical applications, big data, and data science.

Goals

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

  • 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 epidemiological data
  • Communicate research findings and conclusions (written and oral) in a clear and concise manner
  • Serve as an expert biostatistician on collaborative scientific teams

Student Learning Outcomes

  • Students will demonstrate an overall knowledge and understanding of the core concepts in biostatistics, including the essential skills to conduct research in biostatistics.
  • Students will demonstrate critical thinking skills, the capability to develop conjectures, and the ability to make scholarly contributions.
  • Students will demonstrate mastery of research competencies.