University of Kansas

What you'll study

The programme combines core statistical theory with hands-on computational training and applied projects. Typical topics include probability and statistical inference, linear and generalized linear models, multivariate analysis, time series, categorical data analysis, Bayesian methods and survival analysis. Emphasis is placed on statistical computing and data science tools — for example, programming with R and Python, simulation, and reproducible research workflows. Students also study experimental design, statistical consulting principles and advanced elective topics such as machine learning, spatial statistics or high-dimensional data analysis.

The degree is offered with options for a thesis or a project/non-thesis route. Coursework and a culminating experience (master's thesis, applied project or practicum) allow students to demonstrate both theoretical understanding and practical problem-solving. Many students undertake applied projects in collaboration with faculty across campus or external partners.

Entry requirements

Applicants are expected to hold a bachelor’s degree in statistics, mathematics, engineering, computer science, or a related quantitative discipline. Strong preparation in calculus, linear algebra, probability, and introductory statistics is expected. Typical application materials include official transcripts, a statement of purpose describing academic and professional goals, letters of recommendation, and a current résumé or CV. International applicants must demonstrate English proficiency through an accepted language test unless exempt by university policy. Some applicants may be asked to supply GRE scores or additional supporting evidence of quantitative preparation, depending on departmental guidelines.

Career prospects

Graduates enter a wide range of roles where statistical expertise is essential. Common career paths include statistician or biostatistician in healthcare and pharmaceuticals, data scientist or data analyst in technology and finance, quantitative analyst in consulting and government, and research positions in academia or national laboratories. The programme’s applied focus prepares students for roles that require communicating results to non-specialist stakeholders, implementing reproducible analyses, and deploying statistical models in production environments. Alumni often move into positions at hospitals, research institutes, corporations, public agencies or continue on to doctoral study.

Why study at University of Kansas

The University of Kansas offers a supportive environment with faculty active in both methodological research and applied collaborations. Students benefit from access to the Statistical Consulting Center and interdisciplinary research opportunities with the Medical Center, School of Business, engineering departments and regional industry partners. Small class sizes provide personalised mentoring; strong computing resources and training in contemporary software help graduates be job-ready. The programme’s location offers connections to regional employers and collaborative projects while retaining the academic resources of a major public research university.