MSc Applied Statistics in Health Sciences (online)

Why this course?

Our course is run by academics who work in the health sector as well as in higher education. Statisticians from the Animal and Plant Health Agency (APHA), an Executive Agency of the Department for Environment, Food & Rural Affairs (Defra) as well as those who have extensive experience in working with the National Health Service (NHS) in Scotland, will provide lectures based around real-life problems and data from the health sciences.

The course is entirely delivered online. The course is ideally suited to those working full-time or with other commitments. You can study and complete the modules when it’s most convenient for you – you don’t need to be online at specific times.

Although the program is focused on health, the skill set provided will also equip you with the necessary training to work as an applied statistician in other areas such as insurance, finance, and commerce.

You can also study the MSc in Applied Statistics in Health Sciences full-time on campus.

Entry requirements

Academic requirements/experience

• Minimum second-class (2:2) Honours degree or international equivalent.
• Mathematical training to A Level or equivalent standard.
• Prospective students with relevant experience or appropriate professional qualifications are also welcome to apply.
• For Australia and Canada, normal degrees in relevant disciplines are accepted.

Mathematical knowledge

Applicants are required to have some prior mathematical knowledge, for example, A Level or equivalent, in:

• calculus
• linear algebra
• differential equations

English language requirements

You must have an English language minimum score of IELTS 6.0 (with no component below 5.5).

We offer comprehensive English language courses for students whose IELTS scores are below 6.0. Please see ELTD for full details.

As a university, we now accept many more English language tests in addition to IELTS for overseas applicants, for example, TOEFL and PTE Cambridge.

Please contact the university for more information.

Course content

Compulsory classes

• Foundations of Probability & Statistics (20 credits)
• Data Analytics in R (20 credits)
• Statistical Modelling & Analysis (20 credits)
• Quantitative Risk Analysis (10 credits)
• Survey Design & Analysis (10 credits)
• Medical Statistics (20 credits)
• Effective Statistical Consultancy (10 credits)
• Bayesian Spatial Statistics (10 credits)
• Research project (60 credits)