BSc Mathematics and Statistics with Data Science

Compulsory modules

Year 1

• Real Analysis I: Explore mathematical analysis concepts including inequalities, sequences, series and functions.
• Calculus: Extend your existing knowledge of calculus into two or more dimensions, exploring techniques of ordinary differential equations of the first and second order and learning how programming has mathematical applications.
• Foundations of Mathematics: Gain a solid introduction to fundamental topics in mathematics and develop the necessary skills to study mathematics at university-level. You’ll focus on the concept of sets, functions and various familiar number systems, as well as the importance of proofs and how to construct them.
• Linear Algebra: Learn how to solve systems of linear equations, determine eigenvalues and eigenvectors, and develop the algebra of matrices which are used as a stepping-stone to the more general theory of liner and inner-product spaces.
• Mathematical Communication: Discover the importance of expressing mathematical concepts and results clearly, logically and concisely and how to implement basic problem-solving strategies such as data visualisation, pattern exploration and programming.
• Probability and Statistics: Understand probability and probability distributions, results and techniques for statistical reference and data science, and regression and hypothesis testing.

Year 2

• Differential Equations: Build on your knowledge of ordinary differential equations and explore partial differential equations and their applications. You’ll explore non-constant coefficients, integral and series solutions, Fourier series, the theory of boundary value problems, diffusion equations, wave equations and Laplace’s equation.
• Linear Models and Data Analysis: Gain understanding of the most common models, including multiple linear regression and completely randomised designs, and explore the key principles of planned experiments. Learn how models are applied to practical problems and gain experience of real-life data analysis.
• Probability and Statistical Theory: Uncover the interplay between probability theory and fundamental areas of mathematics, and formulate general real or abstract problems in a probabilistic model.
• Numerical Analysis I: Describe, analyse and implement numerical methods for problems in continuous mathematics, including solution of linear equations and nonlinear scalar equations, interpolation, scalar optimisation and solution of ordinary differential equations.
• Mathematical Modelling and Professional Skills: Develop your problem-solving and independent research skills by applying mathematical modelling techniques to solve real-world problems across a broad range of scientific, engineering and economical areas. You’ll also expand your team-working, presentation, career management, technical, verbal and written communication skills.

Year 3

• Advanced Statistical Modelling: Develop an understanding of situations in which different models are likely to be appropriate, learning more about generalised linear models, repeated measurement data, and traditional and modern approaches to data analysis.
• Methods of Machine Learning: Gain familiarity with the range of methods used in statistical machine learning and demonstrate how these are used in research and industry. You’ll have the opportunity to implement machine learning methods using statistical software and interpret and communicate your findings.
• Portfolio of Projects: Conduct a series of projects on mathematical or statistical topics and develop your technical and professional skills.

These are the modules that we currently offer for 2024/25 entry. They may be subject to change as we regularly review our module offerings to ensure they’re informed by the latest research and teaching methods.

Please note that the University cannot guarantee that all optional modules will be available to all students who may wish to take them.

You can also register your details with us to receive information about your course of interest and study and life at the University of Reading.

Overall, 90% of graduates from Mathematics and Statistics are in work or further study within 15 months of graduation (Based on our analysis of HESA data © HESA 2024, Graduate Outcomes Survey 2021/22; includes first degree Mathematics and Statistics responders).

You could choose to work as a mathematician or statistician for public sector organisations, such as health authorities or the Office for National Statistics, or find a career in the private sector.

Your mathematics degree is well-suited to a range of careers, including:

• accountancy
• financial analysis
• engineering
• modelling
• computing
• actuarial work.