Find out more about studying Statistics MSc at University of Leeds? We've gathered all the key details, entry requirements, modules, fees, and more. Take the next step by booking an open day to explore it for yourself.
MSc - Master of Science
Leeds, Main
Full Time
Sep 2026
1 Year
Data is integral to our society and there’s an ongoing demand for numerate specialists in a broad range of industries. From finance to governmental departments, the emergency services to gaming – the career opportunities that’ll open up to you with a Statistics MSc could be far-reaching. Our Statistics MSc is a flexible Masters degree enabling students from a wide range of backgrounds to both broaden and deepen their understanding of statistics. The course combines in-depth training in mainstream advanced statistical modelling with a broad range of specialisations, including financial mathematics, clinical trials and risk management. You’ll also develop your understanding of research methods in statistics from writing styles to programming skills, preparing you for a wide range of careers in different sectors. You’ll apply these skills in an independent research project. Once you’ve graduated, you’ll be fully equipped with the most up-to-date practices and techniques, alongside the technical skill set you’ll need to pursue an exciting career in a variety of job roles. Why study at Leeds: This Masters degree is accredited by the Royal Statistical Society. Our globally-renowned research conducted right here on campus feeds directly into the course, shaping your learning with the latest thinking in areas such as probability and financial mathematics, modern applied statistics and analysis. Benefit from our School’s close links with organisations like Leeds Institute for Data Analytics, Leeds Institute for Fluid Dynamics and the Alan Turing Institute, the UK’s national institute for data science and artificial intelligence. Advance your knowledge and skills in key areas of statistics and statistical computing. Tailor the degree to suit your specific interests with a large selection of optional modules to choose from, with everything from risk management to mathematical biology, medical statistics to stochastic calculus – plus many more. Put theory into practice by conducting a project which focuses on a topic that matches your interests, giving you the chance to apply the knowledge acquired throughout the course and demonstrate independent research skills necessary for a professional or academic career. Access excellent teaching facilities and computing equipment throughout the school, complemented by social areas and communal problem-solving spaces. Experience expert theoretical and practical teaching delivered by a programme team made up of academics who specialise in a wide range of areas in mathematics and statistics. Be part of a diverse and supportive community of mathematicians from all over the world. Enhance Your Academic and Subject-Specific LanguageAs part of your course, you will have access to the Professional and Academic Communication module that provides valuable insights into studying a postgraduate degree in the UK while helping you develop your academic and subject-specific vocabulary. Through a combination of in-person workshops and independent online study, you will explore the use of technology—such as translation tools and generative AI—to support effective communication. You will also build the language and literacy skills necessary to become a more confident and capable communicator throughout your studies. AccreditationRoyal Statistical SocietyAccreditation is the assurance that a university course meets the quality standards established by the profession for which it prepares its students. This course is accredited by the Royal Statistical Society.
On completion of this module, students should be able to: be taught through research experience the planning, execution and maintenance of a statistics project; present their project as a dissertation, which will be presented orally.
The use of computers in mathematics and statistics has opened up a wide range of tech- niques for studying otherwise intractable problems and for analysing very large data sets. "Statistical computing" is the branch of mathematics which concerns these techniques for situations which either directly involve randomness, or where randomness is used as part of a mathematical model. This module gives an overview of the foundations and basic methods in statistical computing. One of the most important ideas in statistical computing is, that often properties of a stochastic model can be found experimentally, by using a computer to generate many random instances of the model, and then statistically analysing the resulting sample. The resulting methods are called Monte Carlo methods, and discussion of such methods forms the main focus of this module.
