The graduate programs in Biostatistics offers comprehensive course work leading to a Master of Science (Sc.M.); a Master of Arts (A.M.) degree for students in the 5th-year Master's program and Brown's Open Graduate Education Program; and the Doctor of Philosophy (Ph.D.) degrees. 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://www.brown.edu/academics/public-health/biostats/academics/doctoral-program.
The Sc.M. program provides training for application of advanced methodology in professional and academic settings. The Department of Biostatistics offers a 5th-Year Master's (A.M. degree) which 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 https://www.brown.edu/academics/public-health/admissions
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.
Requirements for the ScM
| Required Courses -ScM (7 biostatistics plus PHP 1001 | ||
| PHP 2515 | Fundamentals of Probability and Statistical Inference (OR ) | 1 |
| PHP 2520 | Statistical Inference I | 1 |
| PHP 2514 | Applied Generalized Linear Models | 1 |
| PHP 2516 | Applied Longitudinal Data Analysis (1/2 course ) | .5 |
| PHP 2517 | Applied Multilevel Data Analysis (1/2 course ) | .5 |
| PHP 2550 | Practical Data Analysis | 1 |
| PHP 2560 | Statistical Programming with R | 1 |
| PHP 2610 | Causal Inference and Missing Data | 1 |
| PHP 2650 | Statistical Learning and Big Data | 1 |
| PHP 1001 Scope of Public Health (online course) | ||
| Electives (3 Courses) | ||
| Statistical Electives | ||
| PHP 2030 | Clinical Trials Methodology | 1 |
| PHP 2530 | Bayesian Statistical Methods | 1 |
| PHP 2580 | Statistical Inference II | 1 |
| PHP 2601 | Linear Models | 1 |
| PHP 2602 | Analysis of Lifetime Data | 1 |
| PHP 2605 | Generalized Linear Models | 1 |
| PHP 2620 | Statistical Methods in Bioinformatics, I | 1 |
| PHP 2980 | Graduate Independent Study and Thesis Research | 1-5 |
| PHP 2590 | Design of Experiments | 1 |
| PHP 2670 | Simulation Models for Public Health Decision Making | 1 |
| Epidemiology Electives | ||
| PHP 2120 | Introduction to Methods in Epidemiologic Research | 1 |
| PHP 2150 | Foundations in Epidemiologic Research Methods | 1 |
| PHP 2200 | Intermediate Methods in Epidemiologic Research | 1 |
| Programming and Data Science Electives | ||
| PHP 2561 | Methods in Informatics and Data Science for Health | 1 |
| CSCI 1420 | Machine Learning | 1 |
| CSCI 1470 | Deep Learning | 1 |
| CSCI 1570 | Design and Analysis of Algorithms | 1 |
| CSCI 1810 | Computational Molecular Biology | 1 |
| CSCI 1820 | Algorithmic Foundations of Computational Biology | 1 |
Requirements for the AM
| Required Courses -AM (4 biostatistics plus PHP 1001 | ||
| PHP 2515 | Fundamentals of Probability and Statistical Inference (OR ) | 1 |
| PHP 2514 | Applied Generalized Linear Models | 1 |
| PHP 2550 | Practical Data Analysis | 1 |
| PHP 2560 | Statistical Programming with R | 1 |
| PHP 1001 Scope of Public Health (online course) | ||
| Electives (4 Courses) | ||
| Statistical Electives | ||
| PHP 2030 | Clinical Trials Methodology | 1 |
| PHP 2516 | Applied Longitudinal Data Analysis | .5 |
| PHP 2517 | Applied Multilevel Data Analysis | .5 |
| PHP 2530 | Bayesian Statistical Methods | 1 |
| PHP 2580 | Statistical Inference II | 1 |
| PHP 2601 | Linear Models | 1 |
| PHP 2602 | Analysis of Lifetime 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 |
| PHP 2980 | Graduate Independent Study and Thesis Research | 1-5 |
| PHP 2590 | Design of Experiments | 1 |
| PHP 2670 | Simulation Models for Public Health Decision Making | 1 |
| Epidemiology Electives | ||
| PHP 2120 | Introduction to Methods in Epidemiologic Research | 1 |
| PHP 2150 | Foundations in Epidemiologic Research Methods | 1 |
| PHP 2200 | Intermediate Methods in Epidemiologic Research | 1 |
| Programming and Data Science Electives | ||
| PHP 2561 | Methods in Informatics and Data Science for Health | 1 |
| CSCI 1420 | Machine Learning | 1 |
| CSCI 1470 | Deep Learning | 1 |
| CSCI 1570 | Design and Analysis of Algorithms | 1 |
| CSCI 1810 | Computational Molecular Biology | 1 |
| CSCI 1820 | Algorithmic Foundations of Computational Biology | 1 |