Eastern Washington University

What you'll study

The programme combines core training in probability, mathematical statistics and statistical modelling with specialist coursework in biostatistical methods and applied data analysis. Early semesters emphasise calculus, linear algebra and introductory statistics, progressing to intermediate and advanced statistical theory, regression and multivariate analysis. Practical computing and data-management skills are developed through courses in statistical computing and programming (commonly with R and other industry-standard tools), database concepts, and data visualisation.

• Core statistical theory: probability theory, mathematical statistics, point and interval estimation, hypothesis testing.
• Applied methods: linear and generalized linear models, analysis of variance, categorical data analysis, survival analysis and longitudinal data methods relevant to biomedical studies.
• Quantitative foundations: single and multivariable calculus, linear algebra and introductory real analysis as required for rigorous statistical training.
• Computing and data skills: statistical computing, programming in R (and exposure to other languages), data wrangling, reproducible research practices.
• Biostatistics and health-focused electives: introductory epidemiology, clinical trials design and analysis, bioinformatics or computational biology electives where available.
• Capstone and projects: a senior project, practicum or internship component emphasises hands-on analysis of biomedical or public-health datasets, often in collaboration with local health organisations or research groups.

Entry requirements

Applicants are expected to have completed secondary education with strong performance in mathematics. Successful candidates typically meet the university's general admission standards and demonstrate readiness for university‑level calculus. Recommended preparation includes courses in algebra, pre-calculus or calculus, and exposure to biology or chemistry if pursuing the biostatistics emphasis.

Typical departmental expectations include a minimum cumulative GPA consistent with university admission, and preparation in college-preparatory mathematics. Transfer applicants should provide transcripts from previous post-secondary study; students without calculus ready may be admitted but will need to complete the necessary prerequisites before taking intermediate statistical courses. Prospective students are encouraged to contact the department for advice on course placement and preparation.

Career prospects

Graduates with a bachelor’s in statistics concentrating on biostatistics are well placed for roles that require quantitative analysis of biological or health data. Common entry-level positions include:

• Biostatistician or junior statistical analyst in pharmaceutical or biotech companies
• Data analyst or research assistant in hospitals, public-health organisations and government agencies
• Clinical trials data analyst or clinical research coordinator roles
• Analyst positions in health informatics, medical device companies or health‑tech start-ups

Many graduates also choose to continue with graduate study (master’s or doctoral programmes) in biostatistics, statistics, epidemiology, public health or data science to broaden research opportunities and advance into senior analytic or academic roles.

Why study at Eastern Washington University

Eastern Washington University offers a learning environment with relatively small class sizes and accessible faculty, which benefits students in a mathematically intensive programme. The university’s location provides opportunities for applied experience with regional health systems, public-health departments and research institutions in the Spokane area, supporting internships and capstone projects that involve real biomedical datasets.

Students gain hands-on experience with statistical software and data-management tools, and the department emphasises applied learning through laboratory exercises, collaborative projects and practical communication of statistical results to non-technical audiences. The programme prepares graduates for both immediate employment in health-related data roles and for further postgraduate study in quantitative health sciences.