Mathematics and Statistics
Mathematics and statistics together form one of the most powerful intellectual combinations available to a graduate. Mathematics provides the structural language through which the natural and social sciences are expressed, underpinning everything from physics and engineering to economics and computer science. Statistics provides the tools for collecting, analysing, and interpreting data, allowing us to draw valid conclusions from evidence in the face of uncertainty.
In a world increasingly shaped by the analysis of large datasets and the demand for evidence-based decision-making, this combination is among the most sought-after by employers across a wide range of sectors.
At the University of Leeds, this three-year, full-time degree gives you a rigorous grounding in both pure and applied mathematics alongside core statistical theory and methods, developing your ability to construct proofs, model complex systems, and work with real data. The course unlocks the mathematics and statistics that power science, technology, and real-world decision-making, giving you the foundation for careers in data, finance, research, and beyond. A sandwich year is included, offering a substantial work placement that allows you to apply your skills in a professional environment, and work placements are embedded in the course more broadly.
A year abroad is also available, providing the opportunity to study in a different academic and cultural setting. A typical entry tariff of 152 points reflects the strong mathematical preparation required.
Graduates go on to work as statisticians, data scientists, actuaries, financial analysts, operational researchers, software developers, and mathematical modellers in industries ranging from finance and insurance to healthcare, government, technology, and the environmental sciences. Many also pursue postgraduate study in statistics, mathematics, data science, or quantitative research methods, and the rigour developed in this programme provides a strong foundation for further academic work.