Program Information
Last updated
Last updated
Emilia Bagiella
Alan Weinberg
Presented in a one-year, full-time format, the MS in Biostatistics program offers students rigorous, comprehensive didactic training in high-quality clinical and translational research. Our curriculum provides students with strong quantitative training as well as practical strategies for addressing complex challenges of novel, clinical research. The program also helps students hone their critical thinking skills. The program’s structure provides students with the opportunity to gain excellent mentorship and individualized attention from faculty in biostatistics and a variety of other disciplines.
The Master of Science in Biostatistics program provides students with the fundamental skills required for conducting high-quality clinical and translational research. The curriculum emphasizes strong quantitative training, critical thinking skills, and practical strategies for addressing complex challenges in clinical research.
The Theory and Methods Track is aimed at students whose goal is to work as biostatisticians or data analysts in a clinical, research, or industry setting. It can also be used as a stepping stone to pursuing a PhD in Biostatistics or Epidemiology. Applicants do not need to have a background related to a health or clinical field, but a strong quantitative background is required.
The Clinical Applications Track is designed for clinical and translational investigators who want to acquire knowledge of quantitative methods in clinical research. A strong quantitative background and a degree in Medical Sciences (MD, DDS, DMD, ND, or DO) are required to apply to this track. Each track in the program consists of at least 34 credits and must be completed in one full-time year. There are two parts: a course requirement and a capstone requirement.
Program Learning Objectives Upon successful completion of the MS in Biostatistics program, graduates will be able to:
Apply advanced statistical methods to the design, analysis, and interpretation of clinical and translational research studies, using rigorous and practical approaches grounded in biostatistical theory.
Operationalize conceptual research questions into testable hypotheses and determine the most appropriate analytical methods to evaluate those hypotheses in real-world research settings.
Conduct advanced statistical analyses using modern computational tools and techniques, while demonstrating proficiency in statistical programming and data management.
Engage in critical discourse surrounding data management and research ethics, including responsible conduct of research, data privacy, and the ethical use of statistical methods in health research.
Provide novel methodologic solutions to complex challenges in clinical and translational research, drawing on a strong foundation in quantitative reasoning and statistical innovation.
Critically evaluate and interpret scientific literature, assessing the validity and reliability of statistical methods and study findings.
Communicate statistical concepts and results effectively to diverse audiences—including clinicians, researchers, and stakeholders—using clear, accessible language and visualizations.
Collaborate with interdisciplinary teams in academic, clinical, or industry settings, contributing expert biostatistical knowledge to support evidence-based decision-making.
Integrate knowledge from clinical research-related electives to deepen understanding of study design, implementation, regulatory issues, and broader public health implications.
Communicate and explain statistical concepts to clinicians and public health researchers.
Contribute to improving the health and well-being of populations by supporting the generation of high-quality, ethically grounded, and statistically sound evidence in health research.