BSc Mathematics with Statistics
Entry requirements
A level: AAA or AABB including Mathematics (grade A) IB: Pass, with 36 points overall with 18 at Higher Level, including 6 points from Higher Level Mathematics (Preferred Mathematics module is Analysis and Approaches, but Applications and Interpretation also considered)
About this course
Bachelor of Science in Mathematics with Statistics, a mathematics and mathematics and statistics degree exploring mathematical methods alongside statistical theory and application. Core topics include Programming, Signal Processing, Data Analysis, Statistics, Mathematical Modelling, Project Management, Environmental Analysis, Artificial Intelligence & Machine Learning. Students complete a compulsory final-year project as part of their studies. The first year covers foundational concepts through compulsory modules such as Calculus I, Calculus II, Computational Mathematics, Introduction to Statistics, and Linear Algebra I. The second year progresses into specialized theory and methods with compulsory modules including Analysis, Partial Differential Equations, Statistical Inference, and Statistical Modelling I, alongside optional modules such as Algorithms, Fields and Fluids, Fundamentals of Data Science in R, Geometry and Topology, Graph Theory, Group Theory, Introduction to Operational Research, Numerical Analysis, Stochastic Processes, and Vector Calculus and Complex Variable Theory. The final year focuses on advanced techniques and independent research through compulsory modules like Computational Statistical Inference, Design and Analysis of Experiments, Machine Learning, Mathematics Project, and Statistical Modelling II. Students can further tailor their studies in the final year by choosing from optional modules such as Actuarial Mathematics I, Actuarial Mathematics II, Advanced Fluid Dynamics, Advanced Partial Differential Equations, Algebraic Topology, Complex Analysis, Complex and Integral Transform Methods, Further Number Theory and Cryptography, Galois Theory, Geometry and Data, Hilbert Spaces, Infinite Groups, Learning and Teaching Mathematics, Mathematical Biology, Mathematical Finance, Mathematical Programming, Numerical Partial Differential Equations, Optimization, Project Management, Relativity, Black Holes and Cosmology, Statistical Methods in Insurance, Structure and Dynamics of Networks, and Survival Models.
Modules
- Calculus I
- Calculus II
- Computational Mathematics
- Core Skills for Mathematicians I
- Dynamics and Relativity
- First Year Mathematics Workshop
- Introduction to Statistics
- Linear Algebra I
- Linear Algebra II
- Number Theory
- Analysis
- Core Skills for Mathematicians II
- Partial Differential Equations
- Statistical Inference
- Statistical Modelling I
- Algorithms
- Fields and Fluids
- Fundamentals of Data Science in R
- Geometry and Topology
- Graph Theory
- Group Theory
- Introduction to Operational Research
- Numerical Analysis
- Stochastic Processes
- Vector Calculus and Complex Variable Theory
- Computational Statistical Inference
- Design and Analysis of Experiments
- Machine Learning
- Mathematics Project
- Statistical Modelling II
- Actuarial Mathematics I
- Actuarial Mathematics II
- Advanced Fluid Dynamics
- Advanced Partial Differential Equations
- Algebraic Topology
- Complex Analysis
- Complex and Integral Transform Methods
- Further Number Theory and Cryptography
- Galois Theory
- Geometry and Data
- Hilbert Spaces
- Infinite Groups
- Learning and Teaching Mathematics
- Mathematical Biology
- Mathematical Finance
- Mathematical Programming
- Numerical Partial Differential Equations
- Optimization
- Project Management
- Relativity, Black Holes and Cosmology
- Statistical Methods in Insurance
- Structure and Dynamics of Networks
- Survival Models