Programme/Approved Electives for 2020/21
Available as a Free Standing Elective
This module illustrates the application of statistical techniques to health related research. Methods are applied using data from real-life studies, and the importance of statistics for making healthcare decisions is emphasised. No prior knowledge of medicine or biology is required. The module commences with a revision of hypothesis testing and statistical inference procedures. This is followed by four main topics: epidemiology, survival analysis, clinical trials and meta-analysis. Epidemiology explores how statistical methods are used to identify risk factors for disease onset, and to identify accurate tests for diagnosing and screening disease. A range of techniques (including regression) are described for quantifying the association between a factor (such as, smoking, eating beef, using a mobile phone) and the subsequent development of a disease. Survival analysis looks at the features and analysis of data from studies of long-term patient outcomes, for example time to death in those with cancer, and statistical techniques are described for modelling survival trends and identifying factors that improve survival. Clinical trials are immensely important for evaluating the effectiveness of a new treatment, and their design and analysis are considered in-depth, including randomisation and sample size calculations. Meta-analysis is crucial for evidence-based medicine, as it summarises results from multiple studies to provide overall answers to inform clinical decisions (e.g. about the best treatment to use). Core meta-analysis methods are described, and issues such as publication bias addressed. The module is a perfect foundation for a subsequent postgraduate degree in (Medical) Statistics or Data Science.
The aim of this module is to study the application of specialised statistical techniques to health related research.
Intended Learning Outcomes
demonstrate knowledge of the concepts of hypothesis testing: 1,2demonstrate knowledge of the theory and application of clinical trials: 1,2demonstrate knowledge of survival analysis, including functions of survival time, comparison of survival distributions, and multivariate techniques: 2demonstrate knowledge of the theory and application of diagnostic testing: 1,2demonstrate knowledge of systematic review and meta-analysis methodology, and its application: 2demonstrate knowledge of the science of epidemiology and its applications: 1,2
Lectures: 30 hoursPreparation of coursework: 30 hoursIndependent study: 88 hoursUnseen examination : 2 hours
1: Coursework weighted 20%
Description of Module Assessment
One coursework assignment set approximately midway through moduleAssessment will consist of written coursework, problem sheets or any combination thereof.2: Open Book Examination weighted 80%
2 Hour Online Unseen ExamThe examination paper will consist of no less than five and not more than eight questions all of which are compulsory.