BSc 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
BSc in Mathematics and Statistical Science, a mathematics and mathematics and statistics degree focused on analytical techniques and quantitative methods. Core topics include Programming, Statistics, and Mathematical Modelling. This three-year undergraduate programme holds accreditation from the Royal Statistical Society. The first year establishes core foundations through compulsory study of Algebra 1, Advanced Calculus, and Introduction to Probability and Statistics. The second year expands technical proficiency with compulsory modules such as Probability and Inference, Regression Modelling, and Introduction to Stochastic Processes, alongside optional choices like Analysis 4: Metric Spaces and Decision and Risk. The final year centres on compulsory Statistical Inference supplemented by diverse optional units including Measure Theory, Graph Theory and Combinatorics, and Mathematical Ecology.
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