Statistics
School of Mathematics and Statistics,
Faculty of Science

Course description
This course is accredited by the Royal Statistical Society
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.
Modules
Teaching
There are lectures, tutorials, computing sessions and group work. Most statistics lectures are recorded so you can watch them again later.
Distance learning option
This is taught online with support via email and an online forum. Distance learners also come to the University for residential weeks.
You'll need to be in Sheffield for a few days between late May and early June each year for your exams. You're expected to spend around 20 hours each week on your studies if you're doing the two-year version of the course, and around 12 to 15 hours each week if you're doing the three-year version.
Assessment
Some modules may be continuously assessed through ongoing project work with no examination but most taught modules are assessed by a mixture of examinations and coursework. The assessment of the dissertation module is based entirely on your submitted dissertation.
Duration
- 1 year full-time
- 2-3 years part-time by distance learning
Your career
Students graduate with the specialist modelling and analysis skills employers need to interpret the complex datasets that underpin many 21st century professions – from business, manufacturing and marketing to policymaking, science and healthcare.
If you get a second-class degree or better, you automatically qualify for the Royal Statistical Society Graduate Statistician award – a stepping stone to full professional membership of the RSS and Chartered Statistician status.
Entry requirements
We usually ask for a 2:1 honours degree, or equivalent, with substantial mathematical and statistical components or a pass at an equivalent level in the Graduate Certificate.
English language requirements
Overall IELTS score of 6.5 with a minimum of 6.0 in each component, or equivalent.
Fees and funding
The University of Sheffield has scholarships available to support masters students. Students on our MSc Statistics course often have the costs of their degree covered by their employer.
Apply
You can apply for postgraduate study using our Postgraduate Online Application Form. It's a quick and easy process.
Contact
postgradmaths-enquiry@shef.ac.uk
+44 114 222 3789
The content of our courses is reviewed annually to make sure it's up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research; funding changes; professional accreditation requirements; student or employer feedback; outcomes of reviews; and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption. We are no longer offering unrestricted module choice. If your course included unrestricted modules, your department will provide a list of modules from their own and other subject areas that you can choose from.