Taught course

Statistics

Institution
University of Sheffield · School of Mathematical and Physical Sciences
Qualifications
MSc

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

Develop the skills and knowledge a professional statistician needs to solve problems in a range of industries.

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 time
    24-36 months
    • Distance learningis available for this qualification
    full time
    12 months
    • Campus-based learningis available for this qualification

Course contact details

Name
Postgraduate Admissions Tutor
Email
postgradmaths-enquiry@shef.ac.uk
Phone
+44 114 222 3789