Biostatistics Concentration (BIS)
The M.S. with a concentration in Biostatistics is a two-year program that provides training in clinical trials, epidemiologic methodology, implementation science, data science, statistical genetics, and mathematical models for infectious diseases. In contrast to the more general M.P.H. degree, the M.S. degree emphasizes the mastery of biostatistical skills from the beginning of the plan of study. While graduates of this program may apply to the Ph.D. degree program, the M.S. degree is itself quite marketable as a terminal degree. Part-time enrollment is permitted.
Degree Requirements
The Biostatistics concentration requires the completion of sixteen required and elective courses. These requirements exclude PUBH 550 and PUBH 551, Professional Leadership for Public Health Careers, and BIS 695, the Summer Internship. Note: Half-term courses cannot count as an elective unless an additional half-term course is taken. Additionally, all first-year students must participate in an online public health primer course the summer before their first term. This does not count towards the required courses.
The Graduate School of Arts and Sciences requires an overall grade average of High Pass, including grades of Honors in at least two full-term graduate courses for students enrolled in a two-year program. In order to maintain the minimum average of High Pass, each grade of Pass on the student’s transcript must be balanced by one grade of Honors. Each grade of Fail must be balanced by two grades of Honors. If a student retakes a course in which the student has received a failing grade, only the newer grade will be considered in calculating this average. The initial grade of Fail, however, will remain on the student’s transcript. A grade awarded at the conclusion of a full-year course in which no grade is awarded at the end of the first term would be counted twice in calculating this average.
Curriculum
Required Core Courses
| BIS 527 | Introduction to Health Data Science | 1 |
| BIS 623 | Advanced Regression Models | 1 |
| BIS 695 | Summer Internship in Biostatistics 1 | 0 |
| PUBH 508 | Foundations of Epidemiology and Public Health | 1 |
| PUBH 608 | Foundations of Public Health | 1 |
| PUBH 550 | Professional Leadership for Public Health 1 | 0 |
| PUBH 551 | Professional Leadership for Public Health Careers 1 | 0 |
| S&DS 5410 | Probability Theory | 1 |
| or S&DS 5510 | Stochastic Processes | |
| or S&DS 6000 | Advanced Probability | |
| S&DS 5420 | Theory of Statistics | 1 |
| or S&DS 6100 | Statistical Inference | |
| 1 | Course does not count as a credit. |
Intermediate Elective Courses
Four courses are required. A minimum of three must be from the list below. The additional elective can be taken from either list of intermediate electives below.
| Intermediate Electives | ||
| BIS 537 | Statistical Methods for Causal Inference 1 | 1 |
| BIS 540 | Fundamentals of Clinical Trials | 1 |
| BIS 550 | Topics in Biomedical Informatics and Data Science | 1 |
| BIS 555 | Machine Learning with Biomedical Data 1 | 1 |
| BIS 560 | Introduction to Clinical and Translational Informatics | 1 |
| BIS 565 | The Role of Ethics and Equity in Data Science and AI | 1 |
| BIS 567 | Bayesian Statistics | 1 |
| BIS 568 | Applied Artificial Intelligence in Healthcare | 1 |
| BIS 628 | Longitudinal and Multilevel Data Analysis | 1 |
| BIS 630 | Applied Survival Analysis | 1 |
| BIS 634 | Computational Methods for Informatics | 1 |
| BIS 635 | Deep Learning for Biomedical Data Science | 1 |
| BIS 638 | Clinical Database Management Systems and Ontologies 1 | 1 |
| BIS 640 | User-Centered Design of Digital Health Tools 1 | 1 |
| BIS 645 | Statistical Methods in Human Genetics | 1 |
| BIS 646 | Nonparametric Statistical Methods and Their Applications | 1 |
| BIS 679 | Advanced Statistical Programming in SAS and R | 1 |
| BIS 692 | Statistical Methods in Computational Biology 1 | 1 |
| 1 | This course is for year-two students only. |
| Additional Intermediate Electives | ||
| CB&B 5620 | Modeling Biological Systems II | 1 |
| CB&B 5740 | Biomedical Natural Language Processing: Methods and Applications 1 | 1 |
| CDE 516 | Principles of Epidemiology II | 1 |
| CPSC 5370 | Database Systems | 1 |
| CPSC 5770 | Large Language Models: From Foundations to Modern Practice 1 | 1 |
| EHS 568 | Introduction to GIS for Public Health | 1 |
| EHS 569 | Advanced GIS Workshop 1 | 1 |
| EMD 538 | Quantitative Methods for Infectious Disease Epidemiology | 1 |
| EMD 553 | Transmission Dynamic Models for Understanding Infectious Diseases | 1 |
| HSCI 9200 | Pragmatic Trial Design and Implementation 1 | 3 |
| MGT 611 | Policy Modeling 2 | 2 |
| S&DS 5170 | Applied Machine Learning and Causal Inference 1 | 1 |
| S&DS 5790 | Spatial Statistics | 1 |
| S&DS 6110 | Selected Topics in Statistical Decision Theory 1 | 1 |
| S&DS 6320 | Advanced Optimization Techniques 1 | 1 |
| S&DS 6640 | Information Theory 1 | 1 |
| 1 | This course is for year-two students only. |
| 2 | Course offered in the School of Management |
Advanced Elective Courses: Year Two Only
Students completing the M.S. thesis (BIS 649 and BIS 650) must take one course from the list below.
| BIS 629 | Advanced Methods for Implementation and Prevention Science 1 | 1 |
| BIS 631 | Advanced Topics in Causal Inference Methods 1 | 1 |
| BIS 643 | Theory of Survival Analysis 1 | 1 |
| BIS 691 | Theory of Generalized Linear Models 1 | 1 |
| 1 | This course is for year-two students only. |
Students not completing the M.S. thesis must take one course from the list below and one course from either advanced elective list.
| BIS 629 | Advanced Methods for Implementation and Prevention Science 1 | 1 |
| BIS 631 | Advanced Topics in Causal Inference Methods 1 | 1 |
| BIS 643 | Theory of Survival Analysis 1 | 1 |
| BIS 691 | Theory of Generalized Linear Models 1 | 1 |
| 1 | This course is for year-two students only. |
| Additional Advanced Electives | ||
| CB&B 5760 | Foundations of Real World Data Science: Electronic Health Records 1 | 1 |
| CB&B 7520 | Biomedical Data Science: Mining and Modeling 1 | 1 |
| CPSC 6440 | Geometric and Topological Methods in Machine Learning 1 | 1 |
| S&DS 6000 | Advanced Probability 1,2 | 1 |
| 1 | This course is for year-two students only. |
| 2 | Cannot fulfill elective if taken as a substitute for S&DS 5410. |
In addition to the requirements listed above, students must take two additional electives at the graduate or professional-school level.
Required Integrative Learning/Capstone Experience
M.S. Biostatistics students are required to complete a two-semester capstone experience in the second year. This requirement can be fulfilled by:
- Two semesters of the capstone course: BIS 678 (fall) and BIS 681 (spring); or
- One semester of capstone course BIS 678 and the year-long thesis. Students register for BIS 649 (fall, 1 credit) and BIS 650 (spring, 1 credit).
| BIS 678 | Statistical Practice I | 1 |
| BIS 681 | Statistical Practice II | 1 |
| or BIS 649 | Master’s Thesis Research | |
| or BIS 650 | Master’s Thesis Research | |
Upon receiving an M.S. in the Biostatistics concentration of Public Health, the student will be able to:
- Select from a variety of analytical tools to test statistical hypotheses, interpret results of statistical analyses, and use these results to make relevant inferences from data
- Design efficient computer programs for study management, statistical analysis, as well as presentation using R, SAS, and other programming languages
- Demonstrate oral and written communication and presentation skills to effectively communicate and disseminate results to professional audiences