BSc Mathematics and Statistics
Entry requirements
A level: A*A*A A*A*A (including A*A* in Mathematics and Further Mathematics) or A*AA (including A*A in Mathematics and Further Mathematics) and a suitable performance in an accepted mathematics test or A*AA (including A* in Mathematics) and A in AS-level Further Mathematics and a suitable performance in an accepted mathematics test . IB: 38 with 776 in higher level subjects, including a 7 in Higher Level Mathematics (Analysis & Approaches) or 766 in higher level subjects, including a 7 in Higher Level Mathematics (Analysis & Approaches) and a suitable performance in an accepted mathematics test.
About this course
The BSc (Hons) Mathematics and Statistics is an undergraduate mathematics degree combining mathematical study with statistical methods and data analysis. Core topics include programming, data analysis, statistics, mathematical modelling and machine learning. The final year offers a choice between a group and individual project or an internship project undertaken with an external organisation. Students may also apply to add a placement year or a year abroad, extending the programme to four years. The first year establishes core mathematics through Analysis, Calculus, Linear Algebra and Probability, with compulsory Statistics and Programming modules introducing frequentist and Bayesian statistics and Python. The second year develops these further via Mathematical Methods, Statistical Inference, and Data Science and Statistical Modelling, where datasets are explored and modelled in R; optional modules include Algebra II, Computational Mathematics II and Complex Analysis II. In the final year, students choose either the Group Project and Individual Project or the Internship Project, which involves independent statistics and machine learning work with an external partner. Optional modules at this level must include at least one of Advanced Statistical Modelling or Bayesian Computation and Modelling, with choices such as Decision Theory, Machine Learning and Neural Networks, Fluid Mechanics and Quantum Mechanics.
Modules
- Analysis
- Calculus
- Linear Algebra
- Dynamics and Relativity
- Probability
- Programming
- Statistics
- Discrete Mathematics
- Mathematical Methods
- Statistical Inference
- Data Science and Statistical Modelling
- Example optional modules
- You can choose EITHER:
- BOTH Group Project
- AND Individual Project
- OR Internship Project
- Example optional modules