Curriculum (Ph.D.)

Students in the PhD program must complete 40 credits post-masters as well as a 12-credit doctoral dissertation. 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 PhD program.

Core Courses (12 Credits)
The PhD program is built around the following core courses that provide students with solid grounding in advanced statistical theory and methodology.

  • Probability Theory
  • Advanced Statistical Inference
  • Generalized Linear Models
  • Longitudinal Data Analysis

Electives (15 Credits)
Electives are selected from the list below based on whether a student is interested in biostatistics or bioinformatics.

  • Bayesian Inference
  • Statistical Computing
  • Nonparametric Methods
  • Machine Learning and High Dimensional Data Analysis
  • Computational Biology, Bioinformatics & Big Data
  • Statistical Genetics
  • 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
  • Advanced Survival Data Analysis
  • 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 PhD 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. 

Epidemiology Requirement (3 Credits)
This requirement may be satisfied by completing an advanced epidemiology course (approved by the Departmental Education Committee).

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

Internship Requirement (0 Credits)
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 Credits)
This requirement is met by completing a course in responsible conduct of research.

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

Seminar Requirement (0 Credits)
All PhD 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 10a.m.-11a.m. Speakers include internal faculty, visiting scientists, and senior graduate students.

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.