University of Nottingham

What you'll study

This programme combines core theoretical modules, applied and computational courses, and an independent research project. You will study probability and statistical inference to build a firm theoretical base, alongside applied topics such as regression and generalised linear models, multivariate analysis, time series and longitudinal data, and Bayesian methods.

Structure

• Core modules in probability, inference and regression modelling, providing a rigorous grounding in statistical theory and methodology.
• Modules on computational statistics and programming, covering numerical methods and the practical use of statistical software (commonly R and Python) for simulation, resampling and large-scale data handling.
• Applied options which may include time series analysis, spatial statistics, survival and longitudinal analysis, multivariate methods, machine learning and Bayesian modelling, allowing specialisation according to interests.
• A substantial individual research dissertation or project in statistics, supervised by academic staff, that develops applied modelling, novel methodology or computational implementation.

Teaching is delivered through lectures, problem classes, practical computer sessions and project supervision. Assessment typically combines coursework, computer-based assignments, written exams and the dissertation.

Entry requirements

Applicants are normally expected to have a good honours degree (equivalent to a UK upper second class, 2:1) in a numerate subject such as mathematics, statistics, economics, engineering, physics or a closely related discipline. Demonstrable evidence of strong mathematical and statistical capability—through coursework, previous modules in probability/statistics and experience with quantitative programming—is important.

Overseas applicants should meet equivalent academic standards. If English is not your first language, you will usually need to meet the university's English language requirements (for example, a recognised test score at the level the university specifies for postgraduate masters programmes).

Admissions tutors may consider applicants with alternative backgrounds who can demonstrate sufficient quantitative ability and motivation via relevant work experience, additional courses or bridging modules.

Career prospects

Graduates from the MSc Statistics progress to a wide range of careers that require strong analytical and statistical expertise. Typical destinations include roles as data scientists, statisticians, quantitative analysts, biostatisticians, actuarial trainees, research assistants and consultants. Employers span sectors such as finance, pharmaceuticals and healthcare, government and public policy, technology and software firms, environmental agencies, and academic or industrial research centres.

The programme also provides preparation for further research, including PhD study in statistics, machine learning or applied fields that require advanced quantitative skills.

Why study at University of Nottingham

The University of Nottingham's School of Mathematical Sciences offers an established environment for statistical training, with academic staff active in methodological and applied research. Students benefit from a mix of theoretical teaching and practical, computing-focused training, supervised research projects and access to computing facilities and statistical software.

Nottingham has links with regional and national employers and research partners, helping students gain exposure to real-world problems and potential career routes. The university's postgraduate support services, careers provision and student networks further assist in developing employability, professional skills and onward study opportunities.