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.