Program Overview

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MSc Applied Statistics in Health Sciences (online)

The MSc Applied Statistics in Health Sciences (online) is a part-time, online program designed for those with a background in a broad range of disciplines. The program aims to equip students with skills in problem-solving, data analysis, and statistical software packages.

Key Facts

• Start date: September or January
• Accreditation: Royal Statistical Society: MSc graduates may qualify for GradStat status
• Study mode and duration: online over 2 or 3 years, part-time. Standalone modules can also be taken for CPD purposes or working towards an MSc over a maximum of 5 years.

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.

Programme skills set

On the online Applied Statistics in Health Sciences MSc programme you'll have the opportunity to acquire:

• in-depth knowledge of modern statistical methods used to analyse and visualise real-life data sets, and the experience of how to apply these methods in a professional setting
• skills in using statistical software packages used in government, industry and commerce
• the ability to interpret the output from statistical tests and data analyses, and communicate your findings to a variety of audiences including health professionals, scientists, government officials, managers and stakeholders who may have an interest in the problem
• problem-solving and high numeracy skills widely sought after in the commercial sector
• practical experience of statistical consultancy and how to interact with professionals who require statistical analyses of their data

Accreditation

On successful completion of the MSc, you may be eligible for GradStat status. This may be awarded by submitting a transcript to the Royal Statistical Society as part of the evidence of meeting RSS GradStat criteria.

Department of Mathematics & Statistics

At the heart of the Department of Mathematics & Statistics is the University’s aim of developing useful learning. We're an applied department with many links to industry and government. Most of the academic staff teaching on this course hold joint-appointments with, or are funded by, other organisations. These include APHA, Public Health and Intelligence (Health Protection Scotland), Greater Glasgow and Clyde Health Board, and the Marine Alliance for Science and Technology Scotland. We bridge the gap between academia and real-life. Our research has societal impact.

Learning & teaching

Classes are delivered using the University’s portal ‘MyPlace’ and would be videos that you can watch and complete in your own time, and materials that you can work through at your own pace. There is no requirement to be on campus.

Assessment

All assessment will be undertaken online. The assessment will take the form of large-scale projects where you’ll be asked to demonstrate your knowledge on a real-world data set. Projects will involve writing code, interpreting statistical outputs, and producing a report, or presentation outlining the findings from your analysis. Group work may be undertaken in some classes.

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).

Fees & funding

• Tuition fees: £5,600 (3-year programme, price per year), £8,400 (2-year programme, price per year)
• Available scholarships: Scholarships of £1,800 are available to new students joining for January entry of one of our online programmes in the 2025/26 academic year.
• Additional costs: International students may have associated visa and immigration costs.

Careers

There are many exciting career opportunities for graduates in applied statistics. The practical, real-life skills that you'll gain means you'll be much in demand in international organisations. Typical employers of statisticians and data analysts include:

• government
• health services
• pharmaceutical companies
• human, animal, plant and environmental research institutes
• insurance companies
• banks
• internet information providers such as Google
• retailers

Typical graduate roles

Typical job roles of recent graduates include:

• statistician
• data analyst
• statistical programmer
• data scientist

Course content

• Throughout your studies, you will take 80 credits of compulsory taught classes, 40 credits of elective taught classes, and in your final year you'll also undertake your MSc Project (60 credits)
• Compulsory classes:
  • Foundations of Probability & Statistics
  • Data Analytics in R
  • Statistical Modelling & Analysis
  • Medical Statistics
• Elective classes:
  • Quantitative Risk Analysis
  • Bayesian Spatial Statistics
  • Survey Design & Analysis
  • Effective Statistical Consultancy
  • Financial Econometrics
  • Financial Stochastic Processes
  • Data dashboards with RShiny
  • Big Data Tools & Techniques
  • Big Data Fundamentals
  • Machine Learning for Data Analytics

Teaching staff

The following staff are all involved in the teaching and research project supervision (project availability may vary year-to-year).

• Dr Bingzhang Chen
• Dr Tunde Csoban
• Dr Alison Gray
• Dr Helen He
• Dr David Hodge
• Dr Kim Kavanagh
• Dr Louise Kelly
• Prof Adam Kleczkowski
• Dr Ainsley Miller
• Dr Jiazhu Pan
• Prof Chris Robertson
• Dr Ryan Stewart
• Dr Florence Tydeman
• Dr David Young
• Connor Watret
• Dr Suzy Whoriskey
• Dr Yue Wu