12 monthsProgramme duration
31,200 GBPTuition Fee/year
27 Aug, 2026Application Deadline
SepStarting Month
Programme overview
Main Subject
Health/Healthcare
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Ranked 1st globally in THE subject rankings for research quality in clinical and health subjects (THE2025)
The MSc in Medical Statistics and Health Data Science will enable you to engage with the complex statistical and data science healthcare challenges facing the global community, providing exceptional training in statistical and computational methods.
As a medical statistician or health data scientist you will play a vital role in improving the health of populations by conducting statistical research (such as designing clinical trials and epidemiological studies, analysing data and interpreting results) to advance medical knowledge, track or prevent diseases, and improve medications and treatments.
Challenges have arisen over the last decade in the increasing availability of enormous datasets related to human health and healthcare. Health data science combines expertise in epidemiology and statistics with programming / computer science skills to enable analysis of these very large and diverse datasets.
You will be trained in the theory and practice of cutting-edge methods in medical statistics and health data science (for example: causal inference, advanced regression models, infectious disease data analysis and machine learning). Teaching will focus on building strong quantitative and computational skills, and effective interpretation and communication of research findings. Concepts, skills and tools are illustrated using real-life case studies and health-related data. You will gain professional skills such as teamwork, presentation skills, and writing for publication – essential for a successful medical statistician and health data scientist.
Population Health Sciences is a leading centre for research, with numerous opportunities for PhD study and employment on research projects. Internationally recognised for excellence in the development and dissemination of research methodology such as methods for randomised trials and causal inference. You will benefit from this established expertise as a student on the MSc.
This MSc has Royal Statistical Society (RSS) accreditation reflecting the high-quality teaching, learning and assessment within the programme.
Programme overview
Main Subject
Health/Healthcare
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Ranked 1st globally in THE subject rankings for research quality in clinical and health subjects (THE2025)
The MSc in Medical Statistics and Health Data Science will enable you to engage with the complex statistical and data science healthcare challenges facing the global community, providing exceptional training in statistical and computational methods.
As a medical statistician or health data scientist you will play a vital role in improving the health of populations by conducting statistical research (such as designing clinical trials and epidemiological studies, analysing data and interpreting results) to advance medical knowledge, track or prevent diseases, and improve medications and treatments.
Challenges have arisen over the last decade in the increasing availability of enormous datasets related to human health and healthcare. Health data science combines expertise in epidemiology and statistics with programming / computer science skills to enable analysis of these very large and diverse datasets.
You will be trained in the theory and practice of cutting-edge methods in medical statistics and health data science (for example: causal inference, advanced regression models, infectious disease data analysis and machine learning). Teaching will focus on building strong quantitative and computational skills, and effective interpretation and communication of research findings. Concepts, skills and tools are illustrated using real-life case studies and health-related data. You will gain professional skills such as teamwork, presentation skills, and writing for publication – essential for a successful medical statistician and health data scientist.
Population Health Sciences is a leading centre for research, with numerous opportunities for PhD study and employment on research projects. Internationally recognised for excellence in the development and dissemination of research methodology such as methods for randomised trials and causal inference. You will benefit from this established expertise as a student on the MSc.
This MSc has Royal Statistical Society (RSS) accreditation reflecting the high-quality teaching, learning and assessment within the programme.
Admission Requirements
OR
- If your degree subject is not listed above, you will typically need an upper second-class honours degree or an international equivalent, and you will also need:
Either:
- A-level Mathematics (or international equivalent) at grade A or above.
- Three quantitative modules at 60% or above (or an international equivalent), including: Algebra, Calculus, Financial Maths, Maths, Pure Maths, Business Mathematics, Business Statistics, Econometrics, Financial Modelling, Probability, Quantitative Methods, Quantitative Research Methods, Statistics/Statistical Methods/Statistical Analysis, Cost Analysis, Decision Analysis and Simulation, Economics, Financial Analysis, Game Theory, Macroeconomics, Microeconomics, or Engineering Maths.
- A-level Mathematics (or international equivalent) a grade C or above.
We will consider your application if your interim grades are currently slightly lower than the programme's entry requirements and may make you an aspirational offer. This offer would be at the standard level, so you would need to achieve the standard entry requirements by the end of your degree. Specific module requirements would still apply.
We will also consider your application if your final overall achieved grade is slightly lower than the programme's entry requirement.
If your achieved grade is lower than our entry requirements, your application may be more likely to receive an offer if you have additional relevant work experience or qualifications. If you have at least one of the following, please include your CV (curriculum vitae / résumé) when you apply, showing:
- Evidence of relevant work experience such as a Statistician or Quantitative Analyst/Researcher (university or industry), Statistical Programmer, Data Scientist or Accounting, Finance, Actuarial Science, Computer Programmer.
- A postgraduate qualification in Aeronautical Engineering, Aerospace Engineering, Astrophysics, Chemical Engineering, Computer Science, Computing, Data Science, Electrical Engineering, Electronic Engineering, Mathematics, Mechanical Engineering, Nuclear Engineering, Operational Research, Physics, Statistics, or Systems Engineering.
Specific module requirements would still apply.
English language requirements
If English is not your first language, you will need to reach the requirements outlined in our profile level B.
- Candidates are required to submit references or letter(s) of recommendation for acceptance
- Candidates are required to submit an essay(s) for acceptance
Tuition fees
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