Statistics with Medical Applications
Entry requirements
Minimum 2:1 undergraduate honours degree in a relevant subject with relevant modules.
Subject requirements
We accept degrees in the following subject areas:
- Data Science
- Mathematics
- Statistics
We may consider other related degree subjects.
Module requirements
You should have studied at least one module from the following areas:
Area 1: Mathematics
- Algebra / Linear Algebra
- Calculus
- Mathematics Methods
Area 2: Probability
- Markov chains/processes
- Probability theory/modelling
- Stochastic processes/models/modelling
Area 3: Statistics
- Applied statistics
- Bayesian statistics
- Computational statistics
- Data mining/analysis
- Econometrics
- Linear models / generalised linear models
- Medical statistics
- Multivariate statistics / multivariable statistics
- Non-parametric statistics
- Programming languages (e.g. R, Python)
- Sampling / survey design
- Statistical analysis/experiment/modelling
- Statistical software/computing
- Time series
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