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Statistical science skills are powerful tools that play a valuable role in all pure and applied sciences as well as in finance, law and marketing. The quantitative skills training provided by this MSc can lead to new and exciting opportunities in industry, medicine, government, commerce or research.
Key information
Programme starts
September 2020
Modes and duration
Studying on a part-time basis involves spreading the taught modules over two years, but with the same teaching times as for full-time students (i.e. Monday-Friday during the daytime).
Application dates
Tuition fees (2020/21)
Note on fees:
The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website.
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.
English language requirements
If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.
The English language level for this programme is: Standard
Further information can be found on our English language requirements page.
International students
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.
Select your country:
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.
Students undertake modules to the value of 180 credits.
The programme consists of a foundation module, four core modules (60 credits) four optional modules (60 credits) and a research dissertation (60 credits).
Upon successful completion of 180 credits, you will be awarded a MSc in Statistics.
Compulsory modules
- Foundation Course (not credit bearing)
- Statistical Models and Data Analysis
- Statistical Design of Investigations
- Statistical Computing
- Applied Bayesian Methods
Optional modules
At least two from a choice of Statistical Science modules including:
- Decision and Risk
- Stochastic Systems
- Forecasting
- Statistical Inference (compulsory for students needing to reinforce this area)
- Medical Statistics I
- Medical Statistics II
- Stochastic Methods in Finance I
- Stochastic Methods in Finance II
- Factorial Experimentation
- Selected Topics in Statistics
- Bayesian Methods in Health Economics
- Quantitative Modelling of Operational Risk and Insurance Analytics
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 is subject to change.
Dissertation/report
All MSc students undertake an independent research project, culminating in a dissertation of approximately 10,000–12,000 words.
Teaching and learning
The programme is delivered through a combination of lectures, tutorials and classes, some of which are dedicated to practical work. External organisations deliver technical lectures and seminars where possible. Assessment is through written examination and coursework. The research project is assessed through the dissertation and a 15-minute presentation.
Workshops running during the teaching terms provide preparation for this project and cover the communication of statistics e.g. the presentation of statistical graphs and tables.
Additional costs
Accessibility
Details of the accessibility of UCL buildings can be obtained from AccessAble. Further information can also be obtained from the UCL Student Support & Wellbeing team.
Funding
Scholarships relevant to this department are displayed below.
Brown Family Bursary
- Note:
- Deadline: 14 May 2020
- Value:
- £15,000 (1 year)
- Eligibility:
- UK
- Criteria:
- Based on both academic merit and financial need
For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.
Careers
Graduates typically enter professional employment across a broad range of industry sectors or pursue further academic study.
Employability
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.
Why study this degree at UCL?
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.
Department: Statistical Science
What our students and staff say
"UCL has always had a reputation for encouraging thought that is both unorthodox yet somehow addresses social concerns. Furthermore, UCL is a genuinely interdisciplinary institution in one of the world's most diverse cities. My research, by nature, is interdisciplinary because of the various quantitative tools that I need to apply, for example, statistics for modelling energy prices and economics for capturing the behaviour of stakeholders. "
Dr Afzal Siddiqui
I am the Departmental Graduate Tutor with responsibility for the admission of post-graduate research students. I also supervise M.Sc. projects depending upon student interest.
Departmental Graduate Tutor
"London is one of the world's great cities, and Bloomsbury one of the world's greatest academic quarters – featuring among other things the new Alan Turing Institute for data science. Students will benefit from a high density of academic researchers, scientific and commercial partners at their doorstep, as well as the headquarters of the main UK-based international societies in the field: the Royal Statistical Society and the London Mathematical Society."
Professor Patrick J Wolfe
Statistics MSc
UCL Statistical Science
"UCL Statistical Science was the first independent statistics department to be established worldwide. My research focuses on the development and application of Monte-Carlo methods for model calibration. In an era of big data, mathematical models are becoming increasingly challenging, so fitting a model to observations many times requires developing new computational algorithms that will go far beyond standard techniques."
Alexandros Beskos
Statistics MSc and Statistics (Medical Statistics) MSc
UCL Statistical Science
Application and next steps
Applications
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 £80 for online applications and £105 for paper applications. Further information can be found at: www.ucl.ac.uk/prospective-students/graduate/taught/application.
Who can apply?
The programme is accessible to students with first degrees in a quantitative discipline, (such as mathematics, statistics, physics, chemistry, biology, computer science, engineering or economics) who wish to gain advanced training in statistical theory and applications to enable them to enter specialist employment or academic research.
Application deadlines
- All applicants
- 13 March 2020
Please note that the admissions process is expected to be highly competitive - in the previous cycle we received over 20 applications per available place. Reaching the standard entry requirements therefore provides no guarantee that any offer will be made.
For more information see our Applications page.
Apply nowWhat are we looking for?
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.
UCL is regulated by the Office for Students.
Page last modified on 18 February 2020