MSci Mathematics and Statistical Science
Entry requirements
A level: A*A*A (A*A*A with A*A* in Mathematics and Further Mathematics; or A*AA with A*A in Mathematics and Further Mathematics, in any order, together with a 2 in any STEP Paper or a Distinction in the Mathematics AEA. Biology, Chemistry, Computer Science, Economics, English Language, English Literature, Physics and Statistics preferred.) IB: 40 points (A total of 40 points overall with 20 points in three higher level subjects including 7 in Mathematics; or 39 overall with 19 points in three higher level subjects including 7 in Mathematics together with a 2 in any STEP paper or a distinction in Mathematics AEA. The course will accept higher level ‘Mathematics: Analysis and Approaches’ only. Physics, Statistics, Chemistry, Computer Science, Biology, Economics, English Language, English Literature preferred as third subject.)
About this course
MSci in Mathematics and Statistical Science, a mathematics and mathematics and statistics degree focused on analytical reasoning and advanced quantitative methods. Core topics include Programming, Statistics, and Mathematical Modelling. This four-year course is accredited by the Royal Statistical Society and includes an option for study abroad. The first year covers foundational concepts through Algebra 1, Advanced Calculus, and Introduction to Probability and Statistics. The second year progresses to regression techniques via Regression Modelling, Computing for Practical Statistics, and Probability and Inference, alongside optional choices such as Decision and Risk. The third year builds advanced competence through Statistical Inference, complemented by optional studies in Measure Theory and Biomathematics. The fourth year enables deeper specialisation through modules such as Spectral Theory and Algebraic Geometry, concluding with a substantial final-year research component via Project in Mathematics.
Modules
- Algebra 1
- Algebra 2
- Analysis for Joint Honours Students
- Advanced Calculus
- Programming and Vector Calculus
- Introduction to Probability and Statistics
- Further Probability and Statistics
- Introduction to Practical Statistics
- Analysis 3: Complex Analysis
- Algebra 3: Further Linear Algebra
- Probability and Inference
- Regression Modelling
- Introduction to Stochastic Processes
- Computing for Practical Statistics
- Analysis 4: Metric Spaces
- Algebra 4: Groups and Rings
- Decision and Risk
- Statistical Design and Data Ethics
- Statistical Inference
- Critical Perspectives on Mathematics Education
- Measure Theory
- Functional Analysis
- Multivariable Analysis
- Curves and Surfaces
- Biomathematics
- Mathematical Methods 5
- Combinatorial Optimisation
- Graph Theory and Combinatorics
- Mathematical Ecology
- Advanced Modelling Mathematical Techniques
- Spectral Theory
- Riemannian Geometry
- Topology and Groups
- Lie Groups and Lie Algebras
- Algebraic Geometry
- Waves and Wave Scattering
- Evolutionary Games and Population Genetics
- Project in Mathematics
- Computational and Simulation Methods