The Ph.D. in Biostatistics is an advanced, research-oriented degree program requiring in-depth study and research in a particular area of emphasis within biostatistics.  The core curriculum includes coursework in advanced statistical methods and statistical theory.  Additional coursework will include multivariate methods, linear and generalized linear models, statistical computing, design and analysis of clinical trials, and other advanced statistical methods.  Ph.D. students will also receive training in research ethics hands-on experience in statistical consulting, and gain teaching experience through a formal teaching practicum. Students can take elective courses in epidemiology and other core disciplines in public health. Advanced coursework in bioinformatics is available, in which students learn how to apply and develop advanced statistical methods for the analysis of microarray, genomic, and proteomic data.

Entry Requirements

Requirements include differential, integral calculus, multivariate calculus, and linear algebra. In some cases, a student deficient in entry requirements may be admitted, provided a remediation plan is developed and approved by the faculty. Generally, only students who have successfully completed a master’s degree in statistics, biostatistics, or closely related fields will be considered for acceptance.  A limited number of stipends are available to qualified students on a competitive basis.

Applicants should have strong quantitative aptitude and skills, and they are reviewed based on the following criteria:

  • The strength of their previous coursework is based on grades and coursework, with particular emphasis given to courses in statistics, mathematics, and computer science.
  • Scores on the Graduate Record Exam (GRE) with emphasis placed on the Quantitative component.
  • Three letters of reference from individuals who can provide an assessment of your quantitative skills and potential for success in the PhD program.
  • Goal Letter written by the applicant that describes short and long-term goals related to the PhD program and the Biostatistics profession.


Students pursuing a PhD in Biostatistics on a full-time basis may be provided with tuition waivers. A limited number of research assistantships and graduate fellowships are usually available to qualified students on a competitive basis. Students on research assistantship are expected to work up to 20 hours per week to assist faculty in teaching activities through grading and conducting recitation/lab sessions or active participation in research projects. Graduate fellowships do not carry a service obligation, freeing students to devote more time to their studies. These are offered when available and on a highly competitive basis.


The typical sequence of courses during the 1st year of a Ph.D. program for students entering with a master’s degree in biostatistics or statistics.

Typical First-Year Course Sequence for PhD in Biostatistics
Fall Semester
BIOS 6210 Categorical Data Analysis*
BIOS 7204 Advanced Statistical Theory I*
BIOS BIOS Elective
EPID 6210 Principles of Epidemiology
Spring Semester
BIOS 6212 Survival Analysis*
BIOS 7200 Theory of Linear Models*
BIOS 7202 Generalized Linear Models*
PUBH 6200

PUBH 6221

Essentials in Public Health

Foundation of Public Health Ethics

* Core courses for the PhD degree
 PhD written qualifying examinations are based on material from the core courses listed above (excluding PUBH 6200, PUBH 6221, and EPID 6210) and are usually offered in the early summer following completion.


BIOS 6210 Categorical Data Analysis 3
BIOS 6212 Survival Analysis 3
BIOS 6610 Biostatistical Consulting 2
BIOS 6700 Research Seminar in Biostatistics 4
BIOS 7200 Theory of Linear Models 3
BIOS 7202 Generalized Linear Models 3
BIOS 7204 Advanced Statistical Theory I 3
BIOS 7410 Teaching Practicum in Biostatistics 2
BIOS 7900 Dissertation Research 15
EPID 6210 Principles of Epidemiology 3
PUBH 6200 Essentials of Public Health 3
PUBH 6220 Foundations of Public Health Ethics 1
Methodology Electives 6
Applied Emphasis Electives 6
Other Electives 6
Total 63

Methodology Electives
(at least two courses must be taken)

BIOS 6300 Statistical Computing 3
BIOS 6308 Multivariate Methods 3
BIOS 6316 Stochastic Processes 3
BIOS 6318 Nonparametric Statistics 3
BIOS 7205 Advanced Statistical Theory II 3
BIOS 7302 Mixed Models 3
BIOS 7318 Statistical Learning 3
BIOS 7320 Robust Inference 3

 Applied Emphasis Electives
(at least two courses must be taken)

BIOS 6301 Data Visualization 3
BIOS 6302 Longitudinal Data Analysis 3
BIOS 6304 Design and Analysis of Experiments 3
BIOS 6310 Applied Bayesian Analysis 3
BIOS 6312 Sampling Methods 3
BIOS 6314 Clinical Trials Methodology 3
BIOS 6314 Clinical Trials Methodology 3
BIOS 6320 Time Series Analysis 3
BIOS 6450 Design and Analysis of Exp. Studies 3

Transfer Credit – Candidates for the Doctor of Philosophy degree may receive up to 18 hours of transfer credit at the discretion of the program involved, provided they have completed courses that are comparable to the School of Public Health courses in another graduate-level institution and satisfy the subject matter requirements. No transfer credit is permitted for coursework receiving a grade below B, and transfer of the credit does not reduce the residency requirement.