Statistics with Medical Applications
Entry requirements
Minimum 2:1 undergraduate honours degree in a relevant subject with relevant modules.
We look for applications that demonstrate background within mathematics (particularly calculus and linear algebra), probability (and/or stochastic processes) and statistics (eg Linear modelling, multivariate methods, machine learning, time series etc). Typically we require a selection of modules from each of the three areas to cover each year of undergraduate study and at least 50% of the degree to be in a mathematical subject.
Applications with employment history in statistical or data science fields are also welcomed, including for distance learning courses. In such cases we consider the balance of both relevant parts of the employment history and academic qualifications.
Months of entry
September
Course content
Course description
Our Statistics with Medical Applications MSc 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. You’ll build up your programming and data analysis skills using the statistical computing software R. You can also deepen your understanding of statistics with optional modules, such as time series analysis and machine learning.
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.
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. Distance learning students often come with projects designed by their employer.
You’ll gain skills to help you stand out in the graduate job market, such as planning and researching a project, data acquisition, problem specification, analysis and reporting your findings.
Recent examples of dissertation topics include:
- Modelling recruitment projection in clinical trials with application in trials conducted within the Sheffield Clinical Trials Research Unit
- Longitudinal analysis of outcomes in clinical trials
Accreditation
This course is accredited by the Royal Statistical Society.
Please see our University website for the most up-to-date course information: https://www.sheffield.ac.uk/postgraduate/taught/courses
Information for international students
English language requirements
IELTS 6.5 (with 6 in each component) or University equivalent.
Fees and funding
https://www.sheffield.ac.uk/international/fees-and-funding/tuition-fees
Qualification, course duration and attendance options
- MSc
- part time24 months
- Campus-based learningis available for this qualification
- Distance learningis available for this qualification
- full time12 months
- Campus-based learningis available for this qualification
- Distance learningis available for this qualification
Course contact details
- Name
- Postgraduate Admissions Tutor
- postgradmaths-enquiry@shef.ac.uk
- Phone
- +44 114 222 3789