Curriculum (Ph.D.)

Students in the Ph.D. program must complete 40 credits post-masters including Thesis Research. Admitted students must have completed the course requirements (or equivalents) for the Master’s degree in Biostatistics and have a strong coursework in multivariable calculus and linear algebra. While students may be admitted to the program with a less complete background, they would be expected to achieve this level during the first year of admission to the Ph.D. program.

► Current 2019-2020 DBBB Class Schedule  (Printable PDF)


Core Courses (9 Credits)
The Ph.D. program is built around the following core courses that provide students with solid grounding in advanced statistical theory and methodology.

  • Probability & Large Sample Theory
  • Advanced Statistical Inference
  • Generalized Linear Models

Electives (21 Credits)
Electives are selected from the list below based on whether a student is interested in biostatistics or bioinformatics.

  • Bayesian Inference
  • Longitudinal Data Analysis
  • Statistical Computing
  • Semiparametric Inference
  • Causal Inference
  • Advanced Survival Analysis
  • Statistical Genetics
  • Deep Learning and Artificial Intelligence
  • Nonparametric Methods
  • Machine Learning and High Dimensional Data Analysis
  • Computational Biology, Bioinformatics & Big Data
  • Design and Analysis of Sample Surveys
  • Adaptive Design Clinical Trials and Precision Medicine
  • Large Sample Theory
  • Theory of Linear Models
  • Design and Analysis of Experiments
  • Multivariate Analysis
  • Statistics for Biomedical Imaging Data
  • Statistical Methods in Epidemiology
  • Spatial Statistics
  • Applied Stochastic Processes
  • Pattern Recognition

Cognate Requirement (6 Credits)
A cognate area will be defined as an area of specialized study within the Ph.D. degree, in a health related field. This gives students an opportunity to gain knowledge and expertise in a biomedical research field other than statistics/biostatistics. Students must take a minimum of 6 credits in that cognate area. Courses in mathematics, statistics, biostatistics, computer science, econometrics, and psychometrics do not qualify as cognate courses. 

Bioinformatics Requirement (3 Credits)
This requirement may be satisfied by completing a Bioinformatics course among the elective courses.

Consulting and Data Analysis Requirement (1 Credit)
Students must acquire experience in the planning of experiments, analyzing data, reporting results and establish a collaborative interaction with investigators. 

Thesis Research Requirement (0 Credit)
As a Ph.D. candidate, students are required to conduct independent thesis research that will constitute significant original contribution to the field of Biostatistics, involving the development and evaluation of biostatistical methodology (although the methods are motivated by biomedical research problems).

Internship Requirement (0 Credit)
This requirement is satisfied by completing an internship related to biostatistics, and provides students with practical, hands on training as a biostatistician.

Research Ethics Requirement (0 Credit)
This requirement is met by completing a course in responsible conduct of research.

Professional Skills Requirement (0 Credit)
This requirement is met by completing workshops in writing, presentation, interview skills, statistical report and proposal writing.

Seminar Requirement (0 Credit)
All Ph.D. students are required to attend bi-weekly departmental seminar presentations and discussions of special topics and research results in Biostatistics. The seminars are generally held on the 2nd and 4th Friday of every month at 10 am - 11 am.  Speakers may include internal faculty, visiting faculty, visiting research scientists and senior graduate students.


Year 1, Fall Semester:
Probability and Large Sample Theory (3 credits)
Advanced Statistical Inference (3 credits)
Generalized Linear Models (3 credits)
Department Seminar (0 credit)

Year 1, Spring Semester:
Bayesian Inference*  (3 credits)
Longitudinal Data Analysis*  (3 credits)
Statistical Computing*  (3 credits)
Department Seminar  (0 credit)

Year 2, Fall Semester:
Causal Inference*  (3 credits)
Advanced Survival Analysis*  (3 credits)
Semiparametric Inference*  (3 credits)
Cognate RequirementC  (3 credits)
Department Seminar  (0 credit)

Year 2, Spring Semester:
Statistical Genetics*  (3 credits)
Bioinformatics Requirement** (3 credits)
Cognate RequirementC  (3 credits)
Consulting Lab Requirement  (1 credit)
Department Seminar  (0 credit)

Year 3+, Fall or Spring Semesters:
Department Seminar  (0 credit)
Thesis Research (0 credit)

* Biostatistics Electives
** Bioinformatics Elective
C Cognate Requirements 
(may be taken anytime from Year 2+)