The programme will:
- provide a solid training in mainstream advanced statistical modelling
- expose students to modern developments in Statistics
- be flexible in allowing the student to take a broad range of options, including modules within financial mathematics and statistical bioinformatics
- reflect the research interests of the department including specialized topics in statistical shape analysis and directional data, statistical genetics, and stochastic financial modelling.
At the end of the programme students should:
- be prepared to embark on a programme of research as a research student
- be able to undertake data analysis for a wide variety of statistical problems
- have learned key programming skills, both in data analysis and mathematical typesetting
- be equipped as a statistician for a range of careers in industry, commerce and the public sector
- have learned to express mathematical concepts and statistical analysis in both written and verbal form.
[Learning Outcomes, Transferable (Key) Skills, Assessment]
View Timetable
| Code | Title | Credits | Semester | Pass for Progression |
|---|---|---|---|---|
| MATH5701M | Advanced Statistical Modelling | 15 | Semester 2 (Jan to Jun) | |
| MATH5702M | Statistical Computing | 15 | Semester 1 (Sep to Jan) | |
| MATH5703M | Statistical Theory | 15 | Semester 1 (Sep to Jan) | |
| MATH5706M | Further Models for Data Analysis | 15 | Semester 2 (Jan to Jun) | |
| MATH5710M | Project Skills for Statistics and Finance | 15 | Semester 2 (Jan to Jun) | |
| MATH5750M | Project in Statistics | 60 | 1 Jun to 30 Sep | PFP |
Candidates will be required to select 2 modules from list A and 1 module from list B.
Candidates will be required to select 2 modules from list A and 1 module from list B.
List A
| Code | Title | Credits | Semester | Pass for Progression |
|---|---|---|---|---|
| MATH5320M | Discrete Time Finance | 15 | Semester 1 (Sep to Jan) | |
| MATH5340M | Risk Management | 15 | Semester 2 (Jan to Jun) | |
| MATH5420M | Evolutionary Dynamics | 15 | Semester 1 (Sep to Jan) | |
| MATH5705M | Multivariate Data Analysis | 15 | Semester 1 (Sep to Jan) |
List B
| Code | Title | Credits | Semester | Pass for Progression |
|---|---|---|---|---|
| MATH5330M | Continuous Time Finance | 15 | Semester 2 (Jan to Jun) | |
| MATH5350M | Computations in Finance | 15 | Semester 2 (Jan to Jun) | |
| MATH5704M | Time Series Data Analysis | 15 | Semester 2 (Jan to Jun) |
Candidates may choose to take up to 20 credits of elective/Discovery modules at Level 3 or 5M, which should normally include a substantive statistical component, and are subject to the written approval of the Programme Manager.
Last updated: 12/05/2026 16:42:23
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