- UCAS course code
- G101
- UCAS institution code
- M20
Bachelor of Science (BSc)
BSc Mathematics with Placement Year
- Typical A-level offer: A*AA including specific subjects
- Typical contextual A-level offer: A*AB including specific subjects
- Refugee/care-experienced offer: A*BB including specific subjects
- Typical International Baccalaureate offer: 37 points overall with 7,6,6 at HL, including specific requirements
Fees and funding
Fees
Tuition fees for home students commencing their studies in September 2025 will be £9,535 per annum (subject to Parliamentary approval). Tuition fees for international students will be £34,500 per annum. For general information please see the undergraduate finance pages.
Policy on additional costs
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).
Course unit details:
Medical Statistics
Unit code | MATH38072 |
---|---|
Credit rating | 10 |
Unit level | Level 3 |
Teaching period(s) | Semester 2 |
Available as a free choice unit? | No |
Overview
Randomised controlled trials are planned experimental studies on human subjects designed to assess the benefit of medical treatments. Other important areas of application of statistical methods in medical research are epidemiological studies, which investigate the possible causes of disease from observational data, diagnostic studies, which methods of disease diagnosis and meta-analysis, which considers combining information from multiple studies. Many of the major developments in modern statistics have been motivated by problems in medical research. Whilst briefly outlining other areas of application in medical research, the lecture course will introduce the statistical issue associated design and analysis of randomised controlled trials and in meta-analyses.
Pre/co-requisites
Unit title | Unit code | Requirement type | Description |
---|---|---|---|
Probability and Statistics 2 | MATH27720 | Pre-Requisite | Compulsory |
Aims
This course unit introduces the application of statistical ideas and methodology to medical research.
Learning outcomes
On successful completion of this course unit students will be able to:
- Appraise the design, analysis and interpretation of the results of randomised controlled trials (RCTs), with specific reference to minimising bias.
- Choose, with justification, the design, including calculation of the sample size, for a RCT with a continuous or binary outcome.
- 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.
- Derive key mathematical expressions with applications to RCTs or meta-analyses of RCTs.
Syllabus
- Introduction to medical statistics. Randomised controlled trials: historical background and ethical issues concerning randomised experimentation on human subjects.
- Design and organisation of randomised controlled trials. Types of bias and methods for controlling bias including blinding and placebo treatments.
- Sample size estimation for continuous and binary outcome measures.
- Methods of treatment allocation including simple randomization, random permuted blocks, stratification and minimization.
- Implications of equivalence and non-inferiority hypotheses for sample size and statistical analyses.
- 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.
- Multiplicity issues: sub-group analysis and multiple outcomes.
- Alternatives designs for randomised controlled trials: cross-over trials and cluster randomised trials.
- Meta-analysis and publication bias.
Assessment methods
Method | Weight |
---|---|
Other | 20% |
Written exam | 80% |
- Coursework: weighting 20%
- End of semester examination: weighting 80%
Feedback methods
Feedback tutorials will provide an opportunity for students' work to be discussed and provide feedback on their understanding. Coursework or in-class tests (where applicable) also provide an opportunity for students to receive feedback. Students can also get feedback on their understanding directly from the lecturer, for example during the lecturer's office hour.
Recommended reading
- Matthews, JNS, An Introduction to Randomized Controlled Clinical Trials, 2nd edition 2006, Chapman & Hall/CRCPress
The first edition (2000) is also adequate for this course and there are copies of both in the John Rylands Library
Study hours
Scheduled activity hours | |
---|---|
Lectures | 12 |
Tutorials | 12 |
Independent study hours | |
---|---|
Independent study | 76 |
Teaching staff
Staff member | Role |
---|---|
Jack Wilkinson | Unit coordinator |
Additional notes
The independent study hours will normally comprise the following. During each week of the taught part of the semester:
- You will normally have approximately 60-75 minutes of video content. Normally you would spend approximately 2-2.5 hrs per week studying this content independently
- You will normally have exercise or problem sheets, on which you might spend approximately 1.5hrs per week
- There may be other tasks assigned to you on Blackboard, for example short quizzes or short-answer formative exercises
- In some weeks you may be preparing coursework or revising for mid-semester tests
Together with the timetabled classes, you should be spending approximately 6 hours per week on this course unit.
The remaining independent study time comprises revision for and taking the end-of-semester assessment.
The above times are indicative only and may vary depending on the week and the course unit. More information can be found on the course unit’s Blackboard page.