MSc Health Data Science

For entry in the academic year beginning September 2026, the tuition fees are as follows:

• MSc (full-time)
  UK students (per annum): £15,800
  International, including EU, students (per annum): £35,700
• PGDip (full-time)
  UK students (per annum): £12,600
  International, including EU, students (per annum): £28,600
• PGDip (part-time)
  UK students (per annum): £6,300
  International, including EU, students (per annum): £14,300
• PGCert (full-time)
  UK students (per annum): £6,300
  International, including EU, students (per annum): £14,300
• PGCert (part-time)
  UK students (per annum): £3,150
  International, including EU, students (per annum): £7,150

Further information for EU students can be found on our dedicated EU page.

The course fees include all the tuition, technical support and examinations required for the course. All fees for entry will be subject to yearly review. Courses lasting more than one year may be subject to incremental rises per annum. For general fees information please visit: postgraduate fees . Always contact the department if you are unsure which fee applies to your qualification award and method of attendance.

The University permits applicants with comparable previous experience to submit an application for consideration of AP(E)L Accreditation Prior (Experiential) Learning. The maximum AP(E)L is 15 credits to a PGCert, 45 credits to a PGDip and 60 credits to a MSc.

If your AP(E)L application is successful, the University charges £30 for every 15 credits of AP(E)L. The overall tuition fee is adjusted and then the administrative charge is applied.

All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

For the latest scholarship and bursary information please visit the fees and funding page .

The Catherine Chisholm scholarship is applicable to students from selected countries for this course. Find out more details on the scholarship page .

The University of Manchester is proud to offer six fully-funded scholarships to Women from Brunei, Cambodia, Indonesia, Lao PDR, Myanmar, the Philippines, Singapore, Thailand or Timor-Leste completing specific master's courses in STEM subjects. Please visit the STEM scholarship page for more information.

This unit aims to introduce the application of statistical ideas and methodology to randomised controlled trials.

This unit aims to introduce the application of statistical ideas and methodology to randomised controlled trials.

• Introduction to the application of statistics to randomised controlled trials (RCTs)
  RCTs: historical background and ethical issues concerning randomised experimentation on human participants.
• Design and organisation of RCTs. Types of bias and methods for controlling bias in RCTs, including blinding and placebo treatments.
• Critical reviewing publications of RCT – key issues.
• Sample size estimation for continuous and binary outcome measures.
• Methods of treatment allocation including simple randomisation, random permuted blocks, stratification and minimisation.
• Statistical methods for the analysis of parallel group trials including methods for the adjustment for baseline data.
• Implications of protocol deviations and the motivation for the intention-to-treat principle
• Use of R statistical software to design and analyse RCT's
   

A blended learning approach will be used throughout the 11 weeks delivering the new content.

Self-directed learning:

Student review of approximately 1.25 hours of online lecture materials per week. Additionally, students are expected to review lecture slides, including attempting accompanying exercises/ examples (including reading journal papers set for review), and reviewing supplementary notes.

Face-to-face contact:

Review session, complementing online lecture material (additional examples); group tutorial, supporting students working through solutions to an exercise sheet.

There will additionally be one revision week (with two hours of face-to-face contact).

Recognise, choose and apply statistical methods appropriate to a trial, based on its design, objectives and outcome measures.

Critically appraise the design, analysis and interpretation of results of randomised controlled trials (RCTs), with specific reference to minimising bias.

Analyse data from RCTs of various designs (including: parallel, crossover or cluster; superiority, non-inferiority or equivalence), including the meta-analysis of several RCTs, and interpret the findings in the relevant context

Choose, with justification, the design, including calculation of the sample size, for a RCT (parallel, crossover or cluster; superiority, non-inferiority or equivalence) with a continuous or binary outcome.

Primary Text

John Matthews. An Introduction to Randomised Controlled Trials. Taylor and Francis London (2nd edition, 2006; 1st edition, 2001).

Supplementary Texts

Michael Campbell, David Machin, Stephen Walters. Medical Statistics. John Wiley London (5th edition, 2021).

Brian Everitt, Andrew Pickles. Statistical Aspects of the Design and Analysis of Clinical Trials. Imperial College Press (Revised edition, 2004).

Examples of journal reports of RCTs that may be used for critical appraisal exercises:

Quist-Paulsen P, Gallefoss F. Randomised controlled trial of smoking cessation intervention after admission for coronary heart disease BMJ 2003; 327:1254.

Melchart D, Streng A et al. Acupuncture in patients with tension-type headache: randomised controlled trial.  BMJ 2005; doi:10.1136/bmj.38512.405440.8F.