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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 high-quality training in statistical and computational methods that are applicable to low-, middle- and high-income settings. 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 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. All 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.
Programme overview
Main Subject
Health/Healthcare
Degree
MSc
Study Level
Masters
Study Mode
On Campus
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 high-quality training in statistical and computational methods that are applicable to low-, middle- and high-income settings. 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 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. All 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.
Admission Requirements
67+
7+
3.3+
95+
An upper second-class honours degree or international equivalent in a subject with a strong quantitative element. Including, but not limited to, degrees in: Mathematics, Statistics, Physics, Computer Science, Operational Research, Electrical and electronic engineering, Economics, Accounting, Aerospace Engineering, Data Science, Computing, Operations Research, Econometrics, Astro Physics, Mechanical Engineering, Aeronautical Engineering, Systems Engineering, Electronic Engineering, Electrical Engineering, Nuclear Engineering. Joint-honours involving those degree topics (e.g. ‘Physics and French” or “Economics and History” are also acceptable.) Degrees should contain a minimum of three quantitative modules at 2:1/60% or international equivalent, such as: Algebra, Calculus, Financial Maths, Maths, Pure Maths, Business Mathematics, Business Statistics, Computer Science (including programming/algorithms), Data Mining/Data Science/ Data Analytics, Econometrics, Financial Modelling, Probability, Quantitative Methods, Quantitative Research Methods, Statistics/Statistical Methods/Statistical Analysis etc., Cost Analysis, Decision Analysis and Simulation, Economics, Financial Analysis, Game Theory, Macroeconomics, Microeconomics, Engineering Maths.
24 Jul 2025
1 Year
Sep
Candidates are required to submit references or letter(s) of recommendation for acceptance
Candidates are required to submit an essay(s) for acceptance
Domestic
15,900 GBP
International
32,500 GBP
Scholarships
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To help students navigate this challenging process, we recommend the following articles:
MSc Medical Statistics and Health Data Science
12 monthsProgramme duration
32,500 GBPTuition Fee/year
24 Jul, 2025Application Deadline
Health/HealthcareMain Subject Area
Programme overview
Main Subject
Health/Healthcare
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Programme overview
Main Subject
Health/Healthcare
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Admission Requirements
Domestic
International
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
How to get a full scholarship
Looking for a fully-funded scholarship to see you into university? Find out how to boost your chances of getting one.
Scholarships to study abroad
Find scholarships to study abroad with our lists of international scholarships – categorized by country, by subject, and by type of student.
Scholarship Applications: Frequently Asked Questions
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Videos & media
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