Modes and duration
- Full-time: 1 year
- Part-time: 2 years
Tuition Fees (2015/16)
- £8,755 (FT) £4,375 (PT)
- £19,360 (FT) £8,755 (PT)
- All applicants:
- 15 March 2015
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: Standard
Further information can be found on our English language requirements page.
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:
The programme uses 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).
- Foundation Course (not credit bearing)
- Statistical Models and Data Analysis
- Statistical Design of Investigations
- Statistical Computing
- Applied Bayesian Methods
- Stochastic Systems
- Statistical Inference
- Medical Statistics I
- Medical Statistics II
- Stochastic Methods in Finance
- Factorial Experimentation
- Selected Topics in Statistics
- Stochastic Methods in Finance II
- Further Modelling with Applications in Health Research
- Decision and Risk
- Quantitative Modelling of Operational Risk and Insurance Analytics
All MSc students undertake an independent research project, culminating in a dissertation of 10,000–12,000 words. Workshops provide preparation for this project, and run during the teaching terms, and cover the communication of statistics e.g. the presentation of statistical graphs and tables.
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.
Some studentship funding may be available from the Department of Statistical Science. Students wishing to apply for this should indicate their interest on the application form.
- 1 year
- Prospective full-time Master's students within the Faculties of the Built Environment, Engineering Science and Mathematical & Physical Sciences.
More scholarships are listed on the scholarships website
Graduates typically enter professional employment across a broad range of industry sectors or have pursue further academic study.
Top career destinations for this degree
- Actuary Analyst, Towers Watson (2012)
- Statistician, Proctor & Gamble (2011)
- Audit Associate, Ernst & Young (2012)
- Credit Analyst, JP Morgan (2011)
- PhD Statistical Science, UCL (2011)
The Statistics MSc provides skills that are currently highly sought after. Graduate 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 the 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 Statistical Science at UCL 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.
The Statistics MSc has been accredited by the Royal Statistical Society. Graduates will automatically be granted the Society's Graduate Statistician status on application to the Society.
Student / staff ratios › 30 staff › 27 taught students › 35 research students
Department: Statistical Science
"My UCL experience has been absolutely fascinating. I have spent most of my academic life in India, where the education system focuses on rote learning. Moving to London was a pleasant change. It gave me the opportunity to interact with researchers and professors from all over the world and was truly an international experience. The emphasis on practical learning and application was very useful. Some of the professors at UCL have been the best I have had in my entire academic life. Mathematically speaking, my learning trajectory has been on the exponential curve."
Mansi KhannaSubject: Statistics MSc
"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, e.g., statistics for modelling energy prices and economics for capturing the behaviour of stakeholders. "
Dr Afzal SiddiquiSubject: 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.
Application and 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.
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.
- All applicants
For more information see our Applications page.Apply now
What 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