University of Nottingham

What you'll study

The programme covers the foundations and modern practice of statistical science, emphasising both theory and applied computational techniques. Typical core modules include Probability and Stochastic Processes, Statistical Inference, Linear and Generalised Linear Models, Bayesian Methods and Multivariate Analysis. Applied and computational modules often include Time Series and Forecasting, Statistical Machine Learning, Advanced Computational Statistics (including MCMC and resampling methods) and Programming for Data Analysis (usually in R and/or Python).

Study is modular and designed for distance learners: you normally take a set of taught modules delivered as online lectures, tutorials and practical assignments, followed by an independent research project or dissertation. The project allows you to work on a substantial applied or methodological topic, supervised remotely by academic staff and supported by online resources and computing facilities.

Entry requirements

Applicants are normally expected to hold a good honours degree in mathematics, statistics or a closely related quantitative discipline such as economics, engineering, computer science or the physical sciences. Candidates with a lower honours degree plus relevant professional experience, or who have completed recognised conversion courses with substantial quantitative content, may also be considered.

For applicants whose first language is not English, a recognised postgraduate-level English language qualification is required. Admission is assessed on the basis of academic transcripts, references and, where relevant, evidence of numeracy and programming experience. International applicants should provide documentary evidence of prior qualifications in line with the university's general admissions guidance.

Career prospects

Graduates of this MSc move into a wide range of roles that require strong statistical and computational skills. Common career destinations include data scientist, statistician, biostatistician, quantitative analyst, research scientist, and roles in market research, public health, insurance and risk modelling. The training also provides a solid foundation for further research and PhD study in statistics, machine learning or related quantitative fields.

Because the programme emphasises practical computation and project work, graduates are equipped to work with real-world data and modern analysis tools, which is valued by employers across industry, government and academia.

Why study at University of Nottingham

The University of Nottingham's School of Mathematical Sciences has a strong profile in statistical research and teaching, with active research groups in areas such as Bayesian statistics, computational methods and applied statistics. The distance learning MSc is designed to deliver this expertise to remote students with flexible study patterns and robust academic support.

Distance learners benefit from the university's online learning environment, access to extensive library and digital resources, remote supervision for the project and institutional careers support. The programme also connects students with a broad alumni network and opportunities for collaboration with researchers across Nottingham's faculties and research centres.