Program Requirements/Course of Study

The Graduate School has several University-wide requirements for all students enrolled in graduate programs at Brown.  Both students and advisors are expected to become familiar with these.  They can be accessed online at:

Within the Department of Biostatistics, the major requirements for the PhD are:

  1. completion of a program of courses covering core areas of required expertise
  2. demonstration of proficiency in teaching
  3. synthesis of a core body of knowledge, evaluated via written examination
  4. demonstration of readiness to undertake original research, via oral presentation and defense of a written dissertation proposal (oral exam)
  5. completion and oral defense of a dissertation that makes an original contribution in the chosen field of study.

The methods for meeting these requirements may differ depending on the individual program of study.

Competencies in biostatistics are divided into four core areas:  theory and foundation of statistical Inference, general biostatistical methods, advanced training in specialized domain areas, and foundation in public health.

Owing to the inherently interdisciplinary nature of biomedical research, Biostatistics’ students are also required to demonstrate competency in a substantive field of application; examples include (but are not limited to) genetics, economics, demography, molecular biology, epidemiology, infectious diseases, and cancer biology.  This competency is demonstrated via the successful completion of at least one graduate course (1000 or 2000 level) in another department or graduate program.  The selection of this course must be approved by the Graduate Program Director.

Specific course requirements are as follows (courses taken at other institutions can be used to meet one or more course requirements):

Required Courses

PHP 2520 Statistical Inference I
PHP 2530 Bayesian Statistical Methods
PHP 2550 Practical Data Analysis
PHP 2580 Statistical Inference II
PHP 2601 Linear Models
PHP 2605 Generalized Linear Models
PHP 2602 Analysis of Lifetime Data
PHP 2610 Causal Inference and Missing Data
PHP 2950 PhD Journal Club * (see Page 19 in the program handbook for details)
PHP 0101 Public Health Overview (No credit, see Page 4 in the program handbook for description)
PHP 2120 Introduction to Methods in Epidemiologic Research

Electives:  (take at least 5, including at least 2 from biostatistics, 1 in substantive field of application)  

PHP 2030 Clinical Trials Methodology
PHP 2603 Analysis of Longitudinal Data
PHP 2604 Statistical Methods for Spatial Data
PHP 2620 Statistical Methods for Bioinformatics
PHP 2650 Statistical Learning and Big Data
PHP 2690 Advanced Topics in Biostatistics
APMA 2610 Recent Applications of Probability/Statistics
APMA 2821 Stochastic Processes on Graphs
APMA 2811 Convex Analysis + Minimization Algorithm  
Qualifying courses in other departments (APMA, ECON, CS), with approval from Graduate Director

Additional Requirements

Teaching Experience (TE) credit (See page 18 in the program handbook for description)
School of Public Health Responsible Conduct in Research Training - 1st Semester

Transfer Credits

Graduate-level academic credit earned outside of and prior to a student’s current degree program at Brown may accelerate the time to the completion of the tuition unit requirement of the degree. PhD students may transfer up to 8 courses. Only advanced coursework taken while the student was a graduate student either at Brown or another institution may be used for graduate credit at Brown. For details, refer to the Graduate School Handbook.    

For a full list of classes that the Department of Biostatistics offers please visit our Courses page.

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