Course summary
Learn how to apply advanced statistical techniques in medicine and healthcare, from epidemiology to clinical trials. Course description This course trains you to use statistical tools that are central to many areas of medicine: from clinical trials, to disease modelling, to measuring patient outcomes. You’ll develop a detailed working knowledge of essential statistical techniques and concepts, including linear and generalised linear modelling, Bayesian statistics and computational methods and build up your programming and data analysis skills using the statistical computing software R. You’ll study how these skills are applied in clinical trials and choose from a range of optional modules that focus on the role of statistics in other areas of medicine, such as epidemiology and evaluating healthcare interventions. There are also optional modules on other topics in statistics, including time series analysis and machine learning. Around one-third of the course is devoted to your dissertation on a medical or healthcare related topic. This may focus on investigating a data set or a more theoretical or methodological topic. The aim is to give you skills to include on your CV, such as planning and researching a project, data acquisition, problem specification, analysis and reporting your findings. Distance learning students often come with projects designed by their employer. Accreditation This course is accredited by the Royal Statistical Society. Please see our University website for the most up-to-date course information.
How to apply
International applicants
Overall IELTS score of 6.5 with a minimum of 6.0 in each component, or equivalent.
Entry requirements
Minimum 2:1 undergraduate honours degree, with substantial mathematical and statistical components. In particular, you should have studied the following topics and performed well in assessments on them (for example, a score of at least 60 per cent). Mathematical Methods for Statistics: ideas and techniques from linear algebra, including multiple integration, differentiation, matrix algebra, the theory of quadratic forms. Probability and Probability Distributions: the laws of probability and of conditional probability, the concepts of random variables and random vectors and their distributions, the methodology for calculating with them; laws of large numbers and central limit phenomena. Basic Statistics: hypothesis testing; point estimation and confidence intervals; likelihood methods; linear modelling; use of statistical software, for example, R. Overall IELTS score of 6.5 with a minimum of 6.0 in each component, or equivalent.
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
Provider information
University of Sheffield
Western Bank
Sheffield
S10 2TN