Statistics MSc

London, Bloomsbury

Statistical science skills are powerful tools that play a valuable role in all pure and applied sciences as well as in finance, commerce and medicine. The quantitative skills training provided by this MSc can lead to new and exciting opportunities in industry, healthcare, government, commerce or research.

UK students International students
Study mode
UK tuition fees (2024/25)
Overseas tuition fees (2024/25)
1 calendar year
2 calendar years
Programme starts
September 2024
Applications accepted
Applicants who require a visa: 16 Oct 2023 – 05 Apr 2024

Applications closed

Applicants who do not require a visa: 16 Oct 2023 – 30 Aug 2024
Applications close at 5pm UK time

Applications open

Entry requirements

A minimum of an upper second-class Bachelor's degree in a quantitative discipline from a UK university or an overseas qualification of an equivalent standard. Knowledge of mathematical methods and linear algebra at university level and familiarity with introductory probability and statistics is required. Relevant professional experience will also be taken into consideration.

The English language level for this programme is: Level 1

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level.

Further information can be found on our English language requirements page.

Equivalent qualifications

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.

International applicants can find out the equivalent qualification for their country by selecting from the list below. Please note that the equivalency will correspond to the broad UK degree classification stated on this page (e.g. upper second-class). Where a specific overall percentage is required in the UK qualification, the international equivalency will be higher than that stated below. Please contact Graduate Admissions should you require further advice.

About this degree

The programme takes a broad-based approach to statistics, providing up-to-date training in the major applications and an excellent balance between theory and application. It covers modern ideas in statistics including applied Bayesian methods, generalised linear modelling and object-oriented statistical computing, together with a grounding in traditional statistical theory and methods.

The programme is also flexible. By selecting an appropriate combination of optional modules and a suitable project, students can choose to specialise in the following areas: biostatistics, applied stochastic modelling, quantitative decision making, quantitative analysis for industry, financial mathematics. The first of these has been formalised as a separate award.

Who this course is for

The programme is accessible to students with undergraduate degrees in a related quantitative discipline (such as mathematics, statistics, economics, actuarial science), who wish to gain advanced training in statistical theory and applications to enable them to enter specialist employment or academic research.

What this course will give you

One of the strengths of UCL Statistical Science is the breadth of expertise on offer; the research interests of staff span the full range from foundations to applications, and make important original contributions to the development of statistical science.

London provides an excellent environment in which to study statistical science, being the home of the Royal Statistical Society as well as a base for a large community of statisticians, both academic and non-academic.

UCL's newly founded Institute for Mathematical and Statistical Sciences aims to be London's leading centre for research, teaching and collaboration in mathematics and statistics, establishing UCL as a global leader and outward-looking centre for the mathematical sciences and its applications.

The foundation of your career

The Statistics MSc provides skills that are currently highly sought after. Graduates receive advanced training in methods and computational tools for data analysis that companies and research organisations value. For instance, the new directives and laws for risk assessments in the banking and insurance industries, as well as the healthcare sector, require statistical experts trained at graduate level. The large amount of data processing in various industries (known as "data deluge") also necessitates cutting-edge knowledge in statistics. As a result, our recent graduates have been offered positions as research analysts or consultants, and job opportunities in these areas are increasing.


Graduates typically enter professional employment across a broad range of industry sectors or pursue further academic study.

Areas of employment include Accountancy and Financial Services, Banking and Investment, and Consultancy with graduates securing positions with a range of employers including Vanguard and WillisTowersWatson.


The Department offers world-class expertise along with strong links to practitioners, and its position within UCL provides breadth of knowledge (for example the UCL institute for Mathematical and Statistical Sciences, the UCL Centre for Computational Statistics and Machine Learning and the Alan Turing Institute). Staff members also collaborate directly with hospitals, power companies, government regulators, and the financial sector. Consequently, postgraduate students have opportunities to engage with external institutions.

There is a possibility of external organisations delivering technical lectures and seminars while the MSc research project list usually includes collaborative projects available with pharmaceutical companies and other industrial partners.


This MSc programme was accredited by the Royal Statistical Society up until 2023/24. The department is in the process of applying to the Royal Statistical Society to renew accreditation.

Teaching and learning

The primary method of communicating information and stimulating interest is through lectures, which provide you with a formal knowledge base from which your understanding can be developed. Understanding of lecture material is reinforced by problem classes, computer workshops and group tutorials, as well as by self-study. Peer-assisted learning, discussion with other students and individual discussion with staff also support the learning process.

Whereas lectures provide the primary vehicle for accumulating a knowledge base, your intellectual, academic and research skills will mainly be developed outside of the lecture theatre, for example, by tackling and discussing problems set on a regular (usually weekly) basis. Some coursework requires you to develop your thinking beyond rote learning, and to link ideas between different modules. You will be encouraged to reason openly through discussion of set problems in tutorials. For some modules, workshops allow you to work on problems individually or in groups, with teaching staff / assistants present to give help. Teaching staff also hold regular "office hours" during which you are welcome to come and ask questions about the material and obtain individual (one-to-one) assistance and feedback.

Practical and transferable skills are developed by the provision of opportunities for hands-on experience through regular workshops and projects. Much of the tuition for statistical computing takes place in computer workshops, which will allow you to learn through active participation. Additional workshops running during the teaching terms provide preparation for the summer research project and cover the communication of statistics, for example, the presentation of statistical graphs and tables. Project supervisors will provide guidance on how to manage an extended task effectively and you are encouraged to monitor your own working practice using a self-assessment questionnaire, as well as to monitor your own progress by self-marking of non-assessed coursework.

All summative assessment is organised at modular level during the academic year in which the module is taken. Most Statistical Science modules employ a combination of end-of-year written examination and coursework to assess your subject-specific knowledge and academic skills, although some modules are entirely coursework based. Statistical project work further assesses your intellectual, academic and research skills by means of word-processed written reports and, in the case of the summer research project, an oral presentation.

Coursework is designed to encourage you to develop your knowledge and skills as each module proceeds. Although not all coursework contributes towards formal assessment, it will provide you with the opportunity to demonstrate your intellectual and practical skills in written responses to problem sheets and in oral responses during tutorials, with feedback mainly presented through tutorials / problem classes / workshops, and on an individual basis on request.

On average it is expected that a student spends 150 hours studying for each 15-credit module. This includes teaching time, private study and coursework. Modules are usually taught in weekly two-hour sessions over 10 weeks each term.


The core material is delivered through a foundation module (to revise basic concepts in probability and statistics) and further compulsory modules. Programming techniques are introduced within the core modules in order to allow students to code their own statistical methods. Students may then place particular emphasis on their application areas of interest by suitable choice of optional modules.

The research project is a consolidation of the MSc’s taught component. Students will normally analyse and interpret data from a real, complex problem, offering the chance to produce viable solutions. Project topics can be selected from a departmental list, or students can make their own suggestions. The list usually includes some collaborative projects available with industrial partners.

The programme is also offered on a part-time basis over two years. The taught modules are split between the first and second years, but within each year the classes for a particular module are the same ones attended by full-time students (i.e. special teaching times are not offered for the part-time programme).

The foundation module is taken at the beginning of the first year. It is recommended that students also take the module Statistical Models and Data Analysis (STAT0028) in the first year, and module prerequisites need to be fulfilled, but otherwise there is some flexibility in the order that the remaining taught modules can be studied. Part-time students submit their project at the end of the second year. It is possible to arrange with the project supervisor to start to work on the project earlier than full-time students, but part time students are not entitled to a higher amount of supervision overall.

Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability are subject to change. Modules that are in use for the current academic year are linked for further information. Where no link is present, further information is not yet available.

Students undertake modules to the value of 180 credits. Upon successful completion of 180 credits, you will be awarded an MSc in Statistics.


Details of the accessibility of UCL buildings can be obtained from AccessAble Further information can also be obtained from the UCL Student Support and Wellbeing team.

Fees and funding

Fees for this course

UK students International students
Fee description Full-time Part-time
Tuition fees (2024/25) £15,100 £7,550
Tuition fees (2024/25) £37,500 £18,750

The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Where the programme is offered on a flexible/modular basis, fees are charged pro-rata to the appropriate full-time Master's fee taken in an academic session. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website:

Additional costs

There are no programme-specific costs.

For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs.

Funding your studies

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.

Brown Family Bursary

Value: £15,000 (1 year)
Criteria Based on both academic merit and financial need
Eligibility: UK

Next steps

Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.

There is an application processing fee for this programme of £90 for online applications and £115 for paper applications. Further information can be found at Application fees.

When we assess your application we would like to learn:

  • why you want to study Statistics at graduate level
  • why you want to study Statistics at UCL
  • what particularly attracts you to this programme
  • how your academic background meets the demands of this programme
  • where you would like to go professionally with your degree

Together with essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this programme match what the programme will deliver.

Please note that the admissions process is expected to be highly competitive - in the previous cycle we received over 15 applications per available place. Reaching the standard entry requirements therefore provides no guarantee that any offer will be made.

Please note that you may submit applications for a maximum of two graduate programmes (or one application for the Law LLM) in any application cycle.

Choose your programme

Please read the Application Guidance before proceeding with your application.

Year of entry: 2024-2025

UCL is regulated by the Office for Students.