The course

UCAS code
Up to 4 years
Delivery type



Statistical data science is at the core of modern data analytics that turn data into intelligence to inform decision-making and solve challenging problems. Applications range from economics and medicine, to social and environmental sciences. This degree covers theoretical and applied elements of modern statistics, and provides training and practical experience in modelling, analysing and interpreting real data required in the economy, industry and research. The early years of the degree cover basic mathematics, probability and statistics. The final years focus on advanced specialist topics in statistical modelling, data science, machine learning, probability and stochastic processes.


Course content

   Detailed course guide
Year 1

Descriptive Statistics; Introduction to University Mathematics; Calculus; Statistical Science, Professional Development Planning and options from a wide choice, including economics and finance subjects.

Year 2

Statistics; Probability; Multivariable Calculus; Linear Algebra; Real Analysis and options from a wide choice, including actuarial subjects.

Year 3

Statistical Inference; Linear and Generalised Linear Models; Stochastic Processes; Analysis of Data; Bayesian Statistics; Survival Models; Statistical Methods for Social Sciences and options from a wide choice, including actuarial and mathematics subjects.

Year 4

Time Series; Simulation and Statistical Computing; Further Statistical Methods; Special Topics in Statistical Modelling (e.g. in Epidemiology, Ecology or Finance); Foundations of Machine Learning; dissertation and options from a wide choice, including actuarial, financial and mathematics subjects.

More in-depth information on the content of the courses listed above, how they are assessed and the learning outcomes can be accessed via our current student portal.

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