Eastern Michigan University

What you'll study

The programme combines core statistical theory and applied biostatistical methods. Core topics include probability and statistical inference, linear and generalized linear models, and computational statistics. Applied and specialised modules typically cover survival analysis, longitudinal data analysis, clinical trial design and analysis, categorical data methods, and Bayesian approaches.

Students also develop practical skills in statistical programming and data management, with hands‑on training in languages and environments commonly used in the field (for example R and SAS), along with instruction in reproducible research practices. The curriculum normally offers a capstone or practicum option where students complete a supervised applied project using real biomedical or public‑health data; a thesis option is usually available for those interested in research and continuation to doctoral study.

Entry requirements

• Bachelor’s degree from an accredited institution, normally in statistics, mathematics, biostatistics, data science, computer science or a related quantitative discipline.
• A solid undergraduate foundation in calculus, linear algebra, introductory probability and statistics; prior coursework in mathematical statistics or regression is desirable.
• A competitive undergraduate GPA (programs typically expect around a 3.0 on a 4.0 scale) and a transcript showing quantitative preparation.
• Application materials generally include a statement of purpose, current résumé/CV and at least two academic or professional letters of recommendation.
• GRE scores may be optional or considered on a case‑by‑case basis—check the programme’s admissions guidance. International applicants must demonstrate English language proficiency through a recognised test unless exempt.
• Relevant professional experience and programming ability (R, SAS, Python) strengthen an application, especially for the practicum or part‑time study routes.

Career prospects

Graduates are prepared for roles as biostatisticians and data analysts in a variety of settings, including pharmaceutical and biotechnology companies, contract research organisations (CROs), hospitals and health systems, public health agencies, academic research centres and medical device firms. Typical job titles include Biostatistician, Clinical Data Analyst, Statistical Programmer, Research Data Scientist and Epidemiology Analyst.

The programme also provides a foundation for further study at the doctoral level for careers in academic research or highly technical industry roles. The emphasis on applied methods and computing makes graduates competitive for positions that require designing and analysing clinical trials, analysing observational health data, and developing predictive and inferential models for biomedical research.

Why study at Eastern Michigan University

• Practical, applied focus: EMU’s graduate statistics offerings emphasise the application of statistical methods to real‑world problems in health and medicine, including practicum and capstone projects that connect students with local research teams and healthcare partners.
• Accessible faculty mentorship: smaller class sizes allow close contact with faculty who have experience in applied biostatistics, statistical computing and collaboration with clinical researchers.
• Regional connections: EMU’s location near Ann Arbor and Detroit provides access to hospitals, public‑health agencies and industry employers for internships, practicum placements and employment.
• Computing resources and training: students receive training in contemporary statistical software and reproducible workflows, preparing them for the technical demands of biostatistics positions.
• Flexibility for working students: the department typically offers scheduling options and part‑time study pathways that accommodate professionals balancing work and graduate study.