University of Strathclyde

What you'll study

This online master's combines core statistical theory with applied modules and computational training. Typical topics include probability and statistical inference, linear and generalized linear models, multivariate analysis, time series and forecasting, Bayesian methods, design of experiments and survival analysis. Emphasis is placed on practical data analysis: modules cover statistical programming (R and Python), data wrangling, reproducible research and the application of machine learning methods for prediction and classification.

The programme is structured around taught modules followed by a substantial applied project or dissertation, allowing you to apply methods to a real dataset or industry problem. Assessments commonly include coursework, lab-based assignments, project reports and a research project that demonstrates competence in both methodology and computational implementation.

Entry requirements

Admission typically requires an undergraduate degree with a substantial quantitative component, such as mathematics, statistics, engineering, physics, computer science or economics. A good UK honours degree (or international equivalent) is normally expected; candidates with a lower-class degree plus relevant professional experience or evidence of quantitative ability may be considered.

Applicants should have a working knowledge of calculus and introductory probability/statistics. Practical experience or familiarity with programming in R, Python or a similar language is advantageous. International applicants whose first language is not English must meet the university's English language requirements.

Career prospects

Graduates move into a wide range of roles that rely on advanced quantitative and computational skills. Common destinations include data scientist, statistician, data analyst, biostatistician, market researcher, risk analyst, and analytics consultant. The applied focus also prepares graduates for roles in public health, finance, engineering, energy, technology and government, as well as for further research or doctoral study.

The programme's emphasis on real data, reproducible workflows and modern software means graduates are equipped to handle end-to-end data projects, from data cleaning and exploratory analysis to model development and communication of results to non-technical stakeholders.

Why study at University of Strathclyde

The University of Strathclyde is known for its strong applied and industry-facing approach. The Department of Mathematics and Statistics provides a research-active environment with expertise across theoretical and applied statistics, computational methods and data science. The online MSc is delivered using interactive learning tools that support part-time study and professional learners, allowing you to balance study with work commitments.

Students benefit from Strathclyde's connections with industry and public-sector partners, opportunities for applied projects with external organisations, and access to a community of researchers and practitioners. The programme is designed to build immediate workplace skills while retaining rigorous foundations in statistical thinking and methodology.