Statistics
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 MSc 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.
Our Statistics MSc includes modules on how to collect data and design experiments, and the role of statistics in clinical trials. You’ll learn how to analyse and draw meaningful conclusions from data, and develop your programming skills using the statistical computing software R.
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. 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.
External clients, such as pharmaceutical companies or sports modelling organisations, often provide dissertation topics. Distance learning students often come with projects designed by their employer.
Recent examples of dissertation topics include:
- Probabilistic Topic Modelling
- Spatio-temporal Modelling of Social Phenomena
- Feature selection for high dimensional data
- Modelling Football Results
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 time24-36 months
- Distance learningis available for this qualification
- full time12 months
- Campus-based learningis available for this qualification
Course contact details
- Name
- Postgraduate Admissions Tutor
- postgradmaths-enquiry@shef.ac.uk
- Phone
- +44 114 222 3789