Medical statistics is a fundamental scientific component of health research. Medical statisticians interact with biomedical researchers, epidemiologists and public health professionals and contribute to the effective translation of scientific research into patient benefits and clinical decision-making. As new biomedical problems emerge, there are exciting challenges in the application of existing tools and the development of new superior models.
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).
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.
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.
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.
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About this degree
The UCL Medical Statistics degree provides students with a sound background in theoretical statistics as well as practical hands-on experience in designing, analysing and interpreting health studies, including trials and observational studies. The taught component equips students with analytical tools for healthcare economic evaluation, and the research project provides experience in using real clinical datasets.
Students undertake modules to the value of 180 credits.
The programme consists of a foundation course, six core modules (90 credits) two optional modules (30 credits) and the research dissertation (60 credits).
Upon successful completion of 180 credits, you will be awarded a MSc in Statistics (Medical Statistics).
- Foundation Course (not credit bearing)
- Statistical Inference
- Statistical Models and Data Analysis
- Medical Statistics I
- Medical Statistics II
- Statistical Computing
- Applied Bayesian Methods
- At least one from:
- Advanced Computational Biology
- Bayesian Methods in Health Economics
- and at least one from:
- Statistical Design of Investigations
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.
All MSc students undertake an individual 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, for example, the presentation of statistical graphs and tables.
Scholarships relevant to this department are displayed below.
- Deadline: 14 May 2020
- £15,000 (1 year)
- 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.
Medical statisticians enable the application of the best possible quantitative methods in health research and assist in the reliable translation of research findings to public and patients’ health care.
The National Institute of Health Research (NIHR) has identified medical statistics as one of the priority areas in their capacity building strategy.
There is an acute shortage of medical statisticians in the UK and employment opportunities are excellent. Recent graduates from this programme have been employed by clinical trials units, the pharmaceutical industry, NHS trusts and universities (e.g. London School of Hygiene & Tropical Medicine, UCL).
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.
UCL is linked with four NHS hospital trusts and hosts three biomedical research centres, four clinical trial units and an Institute of Clinical Trials and Methodology. Established links between UCL Statistical Science, the NIHR UCLH/UCL Biomedical Research Centre and the Clinical Trial Units provide high-quality biomedical projects for Master's students and opportunities for excellent postgraduate teaching and medical research.
Department: Statistical Science
What our students and staff say
"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 BeskosStatistics MSc and Statistics (Medical Statistics) MSc
UCL Statistical Science
"I enjoy teaching, particularly the opportunity to engage with graduate students in statistical science and to help them become more confident and interested in this branch of mathematics. I work on a variety of applied and methodological projects in biostatistics. On the applied side, I contribute statistical expertise to collaborative projects in medical science, such as clinical trials, and large cohort studies in areas such as rheumatology, ophthalmology and neuroscience."
Aidan O'KeefeStatistics MSc, Statistics (Medical Statistics) MSc, Drug Discovery and Development MSc
UCL Statistical Science
"UCL is a world-leading institution with a very strong inter-disciplinary culture. It's also very well connected to both other universities and industry. It has a very long tradition in statistics (it was the first university statistics department in the world!) with a great mix of applied and methodological research. My work focuses on building statistical models for complex processes.The impact of my work depends on the application at hand. In ecological applications, for example, the aim was to improve our understanding of complex biological systems such as the immune system or how animals respond to environmental triggers.I also really enjoy the interaction with our students, from 1st year undergraduates to research students, and the opportunity to teach them, inspire them, and prepare them to be the statisticians of the future."
Dr Ionna ManolopoulouStatistics MSc, Statistics (Medical Statistics) MSc, Data Science (with specialisation in Statistics) MSc
UCL Statistical Science
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.
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 medical statistical theory and applications in order to enter specialist employment or academic research.
- All applicants
- 13 March 2020
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 (Medical Statistics) at graduate level
- why you want to study Statistics (Medical 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.