University of Strathclyde

What you'll study

The programme combines core statistical methodology with modules tailored to health and biomedical applications. You study topics such as regression modelling, survival analysis, longitudinal and multilevel methods, design and analysis of clinical trials, and Bayesian approaches. Modules emphasise practical data analysis using statistical software (principally R) and cover data management, reproducible research, and the interpretation and communication of results for clinical and public-health audiences.

Teaching typically comprises lectures, applied workshops, computer labs and case studies drawn from epidemiology, clinical trials and routine healthcare data. The degree culminates in a substantial research project or dissertation, where you apply methods to a real dataset under academic supervision and produce a written report and oral presentation.

Entry requirements

Applicants normally hold a good honours degree (equivalent to a UK second-class upper / 2:1 or higher) in statistics, mathematics, computing, a quantitative life-science subject, or a related discipline with demonstrable quantitative skills. Applicants with a lower classification but with strong quantitative experience or relevant professional experience in a statistics-related role may be considered.

Typical requirements include prior knowledge of core probability and mathematical statistics and some programming experience (R or another language). International applicants whose first language is not English are required to meet the University's English language standards.

Career prospects

Graduates are prepared for statistical and data-analytical roles in a range of health-related organisations. Common career destinations include clinical trials units, pharmaceutical and biotech companies, NHS analytics teams and health boards, public-health agencies, medical research institutes and contract research organisations. The programme also provides a sound foundation for PhD study in biostatistics, epidemiology or related fields.

Typical job titles held by alumni include biostatistician, clinical trial statistician, data analyst for health services research, epidemiologist (with further training), and research data scientist. The emphasis on applied computing, reproducible workflows and presentation of results is designed to make graduates immediately effective in collaborative, multidisciplinary teams.

Why study at University of Strathclyde

Strathclyde combines a long tradition in statistics and strong interdisciplinary links across health, medicine and data science, giving students access to staff working on applied health-research projects. The department places practical data analysis and problem-solving at the centre of teaching, supported by modern computing facilities and dedicated statistics software teaching spaces.

The University's close connections with NHS staff, research groups and industry partners in Glasgow and the wider region mean students can learn from real-world case studies and explore project collaborations. The MSc balances rigorous method training with an emphasis on communication and transferable skills valued by employers in academic, clinical and commercial health sectors.