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 real analysis and 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.
Months of entry
This course will teach you the theories behind a variety of statistical techniques, and how to apply them in scenarios that professional statisticians face every day.
You’ll develop a detailed working knowledge of important statistical techniques and concepts, including linear and generalised linear modelling, Bayesian statistics, time series and machine learning. You’ll learn how to analyse and draw meaningful conclusions from data, and develop your programming skills using the statistical computing software R.
This course also includes modules on how to collect data and design experiments, and the role of statistics in clinical trials.
Around one-third of the course is devoted to your dissertation. 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.
Dissertation topics are often provided by external clients – for example, pharmaceutical companies or sports modelling organisations. Distance learning students often come with projects designed by their employer.
This course is accredited by the Royal Statistical Society
Please see our University website for the most up-to-date course information.
Information for international students
English language requirements:
Overall IELTS score of 6.5 with a minimum of 6.0 in each component, or equivalent.
For more information about entry requirements for international students, please visit https://www.sheffield.ac.uk/international/applying/postgraduate-taught
Qualification, course duration and attendance options
- part time24-36 months
- Distance learningis available for this qualification
- full time12 months
- Campus-based learningis available for this qualification
Course contact details
- Postgraduate Admissions Tutor
- +44 114 222 3789