Mathematics with Statistics

Mathematics with statistics is a degree that combines the rigour, abstraction and problem-solving depth of pure and applied mathematics with the quantitative methods that allow us to draw reliable inferences from data. Mathematics develops your ability to reason logically, construct proofs, work with abstract structures and apply mathematical tools to a wide range of real-world problems. Statistics brings a specific set of conceptual and computational tools for dealing with uncertainty, variability and evidence, from the foundations of probability theory and statistical inference through to regression, multivariate methods and the analysis of complex datasets.

At Nottingham Trent University, this three-year full-time programme provides a sound mathematical education with a particular emphasis on the statistical methods that are in demand across industry, finance, public health, social science and the commercial world. NTU's strong connections with employers in the Midlands and beyond give the programme a practical context, and the programme is designed to develop both the theoretical grounding and the computational skills that employers expect. The typical entry tariff is around 104 UCAS points.

You will study calculus, linear algebra, probability, mathematical analysis and differential equations alongside core statistics content including statistical inference, regression analysis, experimental design, time series and applied statistical modelling. Programming and data analysis tools are developed alongside the theoretical work, giving you the computational skills to implement statistical methods in software and to work with real datasets. As the programme progresses, you will move into more specialist areas within the mathematical and statistical curriculum.

Graduates of mathematics with statistics programmes are consistently sought across finance, insurance, data science, government statistical services, market research, pharmaceutical research, operational research, engineering and education. The combination of mathematical rigour and statistical expertise makes graduates well suited to the growing range of roles that require both the ability to build quantitative models and the ability to analyse and interpret data. Many graduates pursue professional qualifications in actuarial science, data science or operational research.

Postgraduate study in statistics, data science, applied mathematics or financial mathematics is a well-supported continuation.