The graduate programs in Biostatistics offers comprehensive course work leading to a Master of Science (Sc.M.); a Master of Arts (A.M.); and the Doctor of Philosophy (Ph.D.) degrees. The graduate programs in Biostatistics are designed to provide training in theory, methodology, and practice of statistics in biology, public health, and medical science. The programs provide comprehensive training in theory and methods of biostatistics, but is highly interdisciplinary and requires students to acquire expertise in a field of application. The Ph.D. program is intended to enable graduates to pursue independent programs of research.
Full details for the Biostatistics Doctoral Program can be found at https://brown.edu/biostatistics/biostatistics-graduate-programs/biostatistics-doctoral-program-0.
The Sc.M. and A.M. programs provide training for application of advanced methodology in professional and academic settings. The Department of Biostatistics also offers the Health Data Science track within the Master's of Science degree program and a 5th-Year Master's is available to Brown Undergraduates. Required courses for the Biostatistics Master's degree program are listed below. Additional details can be found on the Department's webpage: https:\\brown.edu\biostatistics
For more information on admission and program requirements, please visit http://www.brown.edu/academics/gradschool/programs/biomed-biostatistics.
|PHP 2515||Fundamentals of Probability and Statistical Inference||1|
|PHP 2560||Statistical Computing I||1|
|PHP 2120||Introduction to Methods in Epidemiologic Research||1|
|PHP 2980||Graduate Independent Study and Thesis Research||1-5|
|Elective Courses (At Least 4)|
|PHP 2030||Clinical Trials Methodology||1|
|PHP 2530||Bayesian Statistical Methods||1|
|PHP 2550||Practical Data Analysis||1|
|PHP 2561||Programming for Health Data Science|
|PHP 2601||Linear Models||1|
|PHP 2602||Analysis of Lifetime Data||1|
|PHP 2603||Analysis of Longitudinal Data||1|
|PHP 2604||Statistical Methods for Spatial Data||1|
|PHP 2605||Generalized Linear Models||1|
|PHP 2610||Causal Inference and Missing Data||1|
|PHP 2620||Statistical Methods in Bioinformatics, I||1|
|PHP 2650||Statistical Learning and Big Data||1|