MSci Mathematics and Statistics
Entry requirements
A level: A*AA. This should include Mathematics grade A or Further Mathematics grade A. The overall offer grades will be lowered to AAA for applicants who achieve both Mathematics and Further Mathematics at grades AA. IB: 38 points overall with 17 points from the best 3 HL subjects including 6 in Mathematics HL (either analysis and approaches or applications and interpretations)
About this course
MSci Hons in Mathematics and Statistics, a mathematics and mathematics and statistics degree centred on mathematical and computational approaches to quantitative analysis and modelling. Core topics include Programming, Data Analysis, Statistics, Mathematical Modelling, Research Methods, and Artificial Intelligence & Machine Learning. The final year features a significant individual project undertaken with supervisor guidance or as part of a collaborative industry placement. The first year introduces fundamental mathematical foundations through compulsory modules such as Matrices and Calculus, Probability and Statistics, Logic and Discrete Mathematics, and Symmetry and Sequences, alongside choices from optional areas like mathematical modelling, computing, economics, and physics. The second year expands into more advanced concepts via Multivariate Probability and Statistics, Applied Data Science, Project Skills, Linear Algebra, and Real Analysis, complemented by a single optional choice. In the third year, studies focus on core areas including Statistical Inference and Statistical Learning and Prediction, while optional modules allow students to explore topics like medical statistics, mathematical finance, and optimisation. The final year emphasises advanced computing and theoretical methods through Computing and Algorithms for Statistics and a major dissertation, accompanied by Master's-level options covering deep learning, clinical trials, and stochastic calculus.
Modules
- Matrices and Calculus
- Probability and Statistics
- Logic and Discrete Mathematics
- Symmetry and Sequences
- Mathematical Modelling and Programming
- Multivariate Calculus
- Computing Essentials: Programming
- Computing for Business Decision Making
- Managing Uncertainty in Business
- Principles of Macroeconomics
- Principles of Microeconomics
- The Physical Universe
- Fields, Matter and Quantum Physics
- Languages
- Foundations of Accounting and Finance
- Multivariate Probability and Statistics
- Applied Data Science
- Project Skills
- Linear Algebra
- Real Analysis
- Mathematics of Artificial Intelligence
- Abstract Algebra
- Complex Analysis
- Intermediate Accounting and Finance
- Statistical Inference
- Statistical Learning and Prediction
- Medical Statistics
- Changepoint and Time Series Analysis
- Environmental Statistics
- Mathematical Finance
- Mathematics of Generative Modelling
- Stochastic Processes
- Dynamic Modelling
- Graph Theory and Algorithms
- Mathematical Cryptography
- Mathematical Education
- Mathematical Education Placement
- Linear Systems
- Optimisation for Machine Learning
- Advanced Accounting and Finance
- Computing and Algorithms for Statistics
- Dissertation
- Advanced Statistical Modelling
- Clinical Trials
- Deep Learning
- Epidemiology and Disease Modelling
- Hidden-Process Models
- Machine Learning
- Probability Theory
- Stochastic Calculus for Finance
- Predictive Modelling
- Survival and Longitudinal Statistics