University of Chicago

What you'll study

The programme builds a solid foundation in probability, mathematical statistics and computational methods, then applies that foundation to problems in biology, medicine and public health. Core topics include probability theory, mathematical statistics, linear models and regression, statistical computing (R and Python), and data analysis. Biostatistics-specific courses cover experimental design for clinical trials, survival analysis, longitudinal data analysis, causal inference for observational studies, and statistical genomics and high-dimensional data methods.

• Core mathematical and statistical theory: probability, theoretical inference, linear algebra and advanced regression techniques.
• Computing and data skills: programming for statistics, numerical methods, reproducible data analysis, and machine learning foundations.
• Biostatistics and applied methods: clinical-trial design and analysis, survival and time-to-event methods, longitudinal and mixed-effects models, causal inference, epidemiologic methods, and omics data analysis.
• Interdisciplinary electives: courses in molecular biology, genetics, epidemiology, public health, and bioinformatics to provide domain knowledge for applied projects.
• Capstone and research opportunities: supervised research projects with faculty in the Department of Statistics or in collaboration with the Biological Sciences Division, hospital partners and research centres; practicum placements in clinical or public-health settings are encouraged.

Entry requirements

Admission to the University of Chicago is competitive and holistic. Successful applicants typically demonstrate strong quantitative preparation and academic achievement. For this programme, applicants should have completed high-school mathematics through calculus; coursework in probability, statistics or multivariable calculus is advantageous. Preparatory coursework or demonstrated interest in biology or chemistry is helpful for the biostatistics track. Prior programming experience (for example in R, Python or MATLAB) is beneficial but not strictly required.

Applicants should present evidence of analytical thinking and quantitative problem-solving through transcripts, recommendation letters and any relevant project work. As with all applicants to the university, extracurricular accomplishments, personal essays and interviews (where applicable) form part of the holistic assessment.

Career prospects

Graduates with a biostatistics emphasis work across academic, clinical and industry settings. Typical entry roles include biostatistician or data analyst in pharmaceutical and biotech companies, clinical-trials statistician, public-health analyst, statistical consultant, and data scientist in healthcare organisations. Many alumni pursue graduate study—master’s or PhD programmes in biostatistics, statistics, epidemiology, public health or related quantitative fields—or professional degrees such as an MD or DDS for clinical research careers.

The programme’s combination of theoretical rigour and applied training prepares students for roles that require strong statistical reasoning, regulatory understanding for clinical research, and computational proficiency for handling high-dimensional biomedical data.

Why study at University of Chicago

The University of Chicago offers a rigorous statistics curriculum paired with close connections to the Biological Sciences Division, medical researchers and local hospitals, enabling authentic interdisciplinary work. Students benefit from small-class interactions with faculty who are active researchers in probability, statistical methodology and biostatistics, and from research centres focused on genomics, computational biology and public health.

The department emphasises both mathematical foundations and hands-on data analysis, with access to computing resources, workshops, and practicum opportunities. The university’s location and professional networks also support internships and collaborations with hospitals, biotech firms and public-health agencies, helping students translate classroom learning into impactful applied experience.