Dartmouth College

What you'll study

The programme builds a core foundation in probability, statistical inference and computational methods, then applies those tools to problems in biology, medicine and public health. Core topics typically include probability theory, mathematical statistics, linear models and regression, experimental design, and statistical computing (R and Python). Biostatistics‑focused modules commonly cover survival analysis, longitudinal data analysis, categorical data methods, causal inference and Bayesian approaches. Students also take complementary courses in biology, genetics, epidemiology and data science to develop domain knowledge.

• Core coursework: probability and mathematical statistics, inference, regression and multivariate analysis, statistical computing.
• Biostatistics electives: survival analysis, longitudinal methods, categorical data analysis, statistical genetics, causal inference and clinical trial design.
• Computational skills: programming for data analysis (R, Python), reproducible research, data management and high‑performance computing basics.
• Capstone and research: options typically include a senior thesis or capstone project with applied data from biomedical collaborators, as well as practicum placements or internships.
• Interdisciplinary study: elective links with Biological Sciences, Epidemiology/Public Health, the Geisel School of Medicine and departments such as Computer Science and Economics.

Entry requirements

Typical applicants have a strong record in secondary school mathematics (calculus) and science; coursework or experience in statistics, computer programming and advanced mathematics (e.g. linear algebra) is highly recommended. Admissions to Dartmouth are selective and consider the whole application: academic preparation, transcripts, letters of recommendation, personal statement and extracurricular engagement, particularly in quantitative or research activities. Students who arrive without prior statistics experience are usually able to begin with introductory courses and then progress to honours‑level work; those with advanced placement in calculus may accelerate into higher‑level statistics and mathematics courses.

Career prospects

Graduates with a biostatistics emphasis are well positioned for careers in healthcare, pharmaceuticals, public health agencies, clinical research organisations and biotech, as well as for roles in government research and non‑profit health organisations. Common job titles include biostatistician, clinical data analyst, epidemiological data scientist, statistical programmer and research consultant. Many graduates also pursue further training through master’s or doctoral programmes in biostatistics, statistics, epidemiology or related fields, or enter professional programmes in medicine and public health.

Why study at Dartmouth College

Dartmouth offers a close‑knit undergraduate environment with strong opportunities for mentored research and interdisciplinary collaboration. Students benefit from proximity to the Geisel School of Medicine and research institutes focused on health policy and clinical practice, enabling authentic applied projects and internships. Small class sizes, access to faculty across mathematics, biology and computer science, and support for senior theses or capstone projects help students develop both the theoretical grounding and practical experience demanded by biostatistics careers.