Eastern Michigan University

What you'll study

The programme emphasises core statistical theory together with applied methods and computing. Typical topics include probability and statistical inference, linear and generalized linear models, multivariate analysis, time series and forecasting, experimental design and categorical data analysis. Applied and computational coursework commonly covers statistical programming (R, Python and/or SAS), resampling and simulation methods, Bayesian statistics, data mining and machine learning techniques.

Students may complete the degree through a combination of required core courses, electives that allow specialisation (for example, biostatistics, environmental statistics, or industrial quality), and a culminating experience. Options for the culminating experience typically include a supervised practicum or internship with an external employer, a capstone project that applies methods to a real dataset, or a research thesis under faculty supervision.

Typical structure

• Core courses in probability, inference and regression-based modelling.
• Advanced electives in multivariate methods, time series, Bayesian analysis and machine learning.
• Statistical computing and data analysis practicum or capstone project.
• Thesis or non-thesis routes depending on career and academic goals.

Entry requirements

Applicants are expected to hold a bachelor’s degree from an accredited institution. A strong quantitative background is required—typical preparation includes undergraduate coursework in calculus, linear algebra, and introductory statistics or probability. Students without a full quantitative background may be admitted conditionally and asked to complete prerequisite bridge courses.

Applications generally require official transcripts, a statement of purpose outlining goals and quantitative experience, and a current résumé or CV. Many applicants also submit letters of recommendation. International applicants must provide proof of English language proficiency where applicable. Prospective students should consult the university’s graduate admissions office for the latest list of required documents and any standardised testing policies.

Career prospects

Graduates are prepared for roles that demand strong statistical and computational skills. Common job titles include statistician, data analyst/scientist, biostatistician, quality analyst, survey methodologist, and analytics consultant. Employers are found across sectors such as healthcare and pharmaceuticals, manufacturing and automotive supply chains, finance, market research, government agencies, and technology firms. The programme’s applied focus and practicum options also support students seeking to transition into industry roles or to strengthen their profile for doctoral study in statistics or related fields.

Why study at Eastern Michigan University

Eastern Michigan University offers a programme with an applied emphasis taught by faculty engaged in both methodological and applied research. Students benefit from small class sizes, direct access to faculty, and training in contemporary statistical software and computing environments. The university’s location near a major metropolitan area provides opportunities for internships and collaborations with regional healthcare organisations, manufacturers and public agencies. Additionally, the department supports practicum arrangements and advising to help students translate classroom skills into practical experience and employment connections.