Southern Methodist University

What you'll study

The programme combines foundational statistical theory with applied biostatistical methods and computing. Typical core topics include probability and statistical inference, linear models and generalized linear models, multivariate analysis, and statistical computing. Biostatistics-focused modules commonly cover survival analysis, longitudinal data analysis, design and analysis of clinical trials, categorical data methods and causal inference.

Practical skills are emphasised: students learn data management and reproducible analysis using R, SAS and/or Python, and work with real biomedical datasets. Electives often allow study in bioinformatics, statistical genetics, clinical trial methodology, machine learning for health data or advanced topics in epidemiology. The degree usually culminates in a capstone project, practicum with a healthcare/industry partner, or a supervised research thesis demonstrating applied biostatistical competence.

Entry requirements

Applicants should hold a recognised bachelor’s degree, typically in statistics, mathematics, biostatistics, computer science, engineering or a closely related quantitative discipline. Preparatory background expected includes multivariable calculus, linear algebra, introductory probability and statistics, and some programming experience (R, Python or similar).

• Official transcripts covering undergraduate coursework.
• A personal statement describing quantitative preparation and interest in biostatistics.
• Curriculum vitae or résumé and at least two academic or professional references.
• Some programmes may request GRE scores, while others make them optional; check the specific requirements of the department.
• International applicants will need to demonstrate English proficiency where applicable.

Career prospects

Graduates typically enter roles as biostatisticians or statistical programmers in pharmaceutical and biotechnology companies, contract research organisations (CROs), academic medical centres, hospitals and public-health agencies. Common responsibilities include designing studies, analysing clinical-trial and observational data, preparing regulatory submissions, developing statistical analysis plans and contributing to interdisciplinary research teams.

Other career paths include positions in medical device companies, health technology and digital health firms, epidemiology units, and further academic research or doctoral study. The training also prepares students for applied data-science roles where expertise in inference, uncertainty quantification and reproducible analysis is valued.

Why study at Southern Methodist University

Southern Methodist University is located in the Dallas–Fort Worth region, offering proximity to a growing healthcare and life-sciences ecosystem and opportunities for internships and collaborations with hospitals, research centres and industry partners. The university’s statistics faculty have strengths in applied methodology and computing, enabling a curriculum that bridges theory and real-world biomedical problems.

Students benefit from access to university computing resources, small cohort sizes that support close faculty mentorship, and cross-disciplinary connections across biomedical, engineering and public-health departments. The programme’s applied focus is designed to prepare graduates for immediate contribution to clinical research teams and industry settings in the region and beyond.