BSc Mathematics and Statistics (Placement Year)
Entry requirements
A level: AAA. This should include Mathematics grade A or Further Mathematics grade A. The overall offer grades will be lowered to AAB for applicants who achieve both Mathematics and Further Mathematics at grades AB, in either order. IB: 36 points overall with 16 points from the best 3 HL subjects including 6 in Mathematics HL (either analysis and approaches or applications and interpretations)
About this course
BSc Hons in Mathematics and Statistics (Placement Year), an undergraduate degree in the Mathematics and Mathematics and Statistics domain, develops advanced quantitative reasoning. Core topics include Programming, Signal Processing, Data Analysis, Statistics, Mathematical Modelling, Accounting, Critical & Analytical Thinking, Human Behaviour, Artificial Intelligence & Machine Learning. Students complete a dedicated professional placement year in industry during their studies. The first year establishes fundamental concepts through compulsory modules such as Matrices and Calculus, Probability and Statistics, Logic and Discrete Mathematics, and Symmetry and Sequences. Year 2 advances analytical capabilities with core studies in Multivariate Probability and Statistics, Applied Data Science, Project Skills, Linear Algebra, and Real Analysis. The final year focuses on advanced methods through compulsory modules including Statistical Inference and Statistical Learning and Prediction. Optional modules across the degree allow specialisation in areas such as financial mathematics, medical statistics, environmental statistics, or machine learning.
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
- Placement
- 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