Statistics MSc

Course overview

Please note: applications for this course open on the 1^st October 2024.

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.

Accreditation

Royal Statistical Society

Accreditation 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

Course details

Please note: applications for this course open on the 1^st October 2024.

The first two semesters of your course will consist of taught modules and in the third semester you'll devote your time to a major dissertation.

You’ll learn a range of statistical computing techniques and develop research skills such as academic writing, programming and literature searches.

Options within the course vary from mainstream topics in statistical methodology to allow you to specialise in the areas of statistics that interest you. Specialist areas within the course include biological or financial applications of statistics, or broad-based statistical expertise.

Course structure

The list shown below represents typical modules/components studied and may change from time to time. Read more in our terms and conditions.

For more information and a full list of typical modules available on this course, please read Statistics MSc in the course catalogue

Compulsory modules

Statistical Computing – 15 credits

This module gives you an overview of the foundations and basic methods in statistical computing. You will learn how to apply standard methods for random number generation, understand the principles and methods of stochastic simulation and apply different Monte Carlo methods. Additionally, you will learn how to use software for advanced statistical computing so you can implement statistical algorithms for a given problem.

Dissertation in Statistics – 60 credits

You’ll be required to complete a research project over the summer. This is an opportunity for you to pursue a particular topic in-depth. Your supervisor will help you to find a project that matches your interests and motivations for studying this degree.

Optional modules

Please note: The modules listed below are indicative of typical options.

• Mathematical Biology – 15 credits
• Evolutionary Modelling – 15 credits
• Linear Regression and Robustness – 15 credits
• Statistical Theory – 15 credits
• Stochastic Calculus for Finance – 15 credits
• Multivariate Analysis – 10 credits
• Time Series – 10 credits
• Introduction to Clinical Trials – 15 credits
• Medical Statistics in Practice – 15 credits
• Mixed Models with Medical Applications – 15 credits
• Discrete Time Finance – 15 credits
• Continuous Time Finance – 15 credits
• Risk Management – 15 credits
• Advanced Mathematical Biology – 20 credits
• Advanced Evolutionary Modelling – 20 credits
• Linear Regression and Robustness and Smoothing – 20 credits
• Multivariate and Cluster Analysis – 15 credits
• Time Series and Spectral Analysis – 15 credits
• Generalised Linear and Additive Models – 15 credits
• Independent Learning and Skills Project – 15 credits

Learning and teaching

Teaching is by lectures, tutorials, seminars and a supervised research project. Extensive use is made of IT and a wide range of materials are available to enhance and extend the material taught formally

On this course you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.

Assessment

The taught course is primarily assessed by end-of-semester examinations with a small component of continuous assessment. The semester 3 project is assessed by a written dissertation and a short oral presentation.

Applying

Entry requirements

A bachelor degree with a 2:1 (hons) in a subject containing a substantial mathematical and statistical component. You’ll have a foundation in statistics including strong grades in statistical modules (no key marks below 2:2). We may ask for further detailed module information if these are not clear on your transcript.

We do not normally accept degrees in Accountancy or Finance.

International

We accept a range of international equivalent qualifications. For more information please contact the Admissions Team.

English language requirements

IELTS 6.5 overall, with no less than 6.0 in all components. For other English qualifications, read English language equivalent qualifications.

Improve your English

International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.

This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Science (6 weeks) and Language for Science: General Science (10 weeks). 

We also offer online pre-sessionals alongside our on-campus pre-sessionals. Find out more about our six week online pre-sessional.

You can also study pre-sessionals for longer periods – read about our postgraduate pre-sessional English courses.

How to apply

Please note: applications for this course open on the 1^st October 2024.

Application deadlines

Applicants are encouraged to apply as early as possible.

30 June 2025 – International applicants

12 September 2025 – UK applicants

If you're still unsure about the application process, contact the admissions team for help.

Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.

Admissions policy

University of Leeds Admissions Policy 2025

This course is taught by

School of Mathematics

Contact us

School of Mathematics Admissions Team

Email: maths-msc@leeds.ac.uk
Telephone:

Fees

UK: £14,000 (Total)

International: £31,250 (Total)

Read more about paying fees and charges.

For fees information for international taught postgraduate students, read Masters fees.

Additional cost information

There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more on our living costs and budgeting page.

Scholarships and financial support

If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government.  Find out more at Masters funding overview.

Career opportunities

There is a shortage of well-qualified statisticians globally. Numeracy, in general, is an attribute keenly sought after by employers. The emergence of data mining and analysis means that demand for statisticians is growing across a wide range of sectors, including:

• Actuarial, betting and gaming industries
• Charitable organisations
• Commercial, environmental and financial organisations
• Forensic and police investigation
• Government departments
• Market research
• Medical and pharmaceutical organisations

The course is designed specifically to meet this demand.

Plus, University of Leeds students are among the top 5 most targeted by top employers according to The Graduate Market 2024, High Fliers Research.

Many statistical careers require people educated to Masters degree level. This course is designed to build on existing mathematical skills and deepen knowledge of statistics in order for you to access a variety of professions or pursue further research as a PhD student.

Here’s an insight into some of the job positions and organisations previous statistics graduates have secured:

• Statistical Consultant, University of Sheffield
• Statistician, Unilever
• Statistician, CSS
• Risk Analyst, Albourne Cyprus Limited
• Bio Statistician, King Khaled Eye Specialist Hospital
• Data Scientist, City Football Group
• Programme Analyst, Journey Further
• Actuary, Xafinity Consulting Ltd
• Data Scientist, IBM
• Assistant Professor-Biostatistics, University of South Florida
• Chief Planning Officer, Health Department-KP

Careers support

At Leeds, we help you to prepare for your future from day one. We have a wide range of careers resources — including our award-winning Employability Team who are in contact with many employers around the country and advertise placements and jobs. They are also on hand to provide guidance and support, ensuring you are prepared to take your next steps after graduation and get you where you want to be.

• Employability events — we run a full range of events including careers fairs in specialist areas and across broader industries — all with employers who are actively recruiting for roles.
• MyCareer system — on your course and after you graduate, you’ll have access to a dedicated careers portal where you can book appointments with our team, get information on careers and see job vacancies and upcoming events.
• Qualified careers consultants — gain guidance, support and information to help you choose a career path. You’ll have access to 1-2-1 meetings and events to learn how to find employers to target, write your CV and cover letter, research before interviews and brush up on your interview skills.
• Opportunities at Leeds — there are plenty of exciting opportunities offered by our Leeds University Union, including volunteering and over 300 clubs and societies to get involved in.

Explore more about your employability opportunities at the University of Leeds:

Find out more about career support.