2019/20 Taught Postgraduate Programme Catalogue
MSc Statistics
| Programme code: | MSC-STAT | UCAS code: | |
|---|---|---|---|
| Duration: | 12 Months | Method of Attendance: | Full Time |
| Programme manager: | Dr Arief Gusnanto | Contact address: | arief@maths.leeds.ac.uk |
Total credits: 180
Entry requirements:
BSc (or equivalent) in a subject containing a substantial mathematical and statistical component, usually at level 2.1 or above (or equivalent).
School/Unit responsible for the parenting of students and programme:
School of Mathematics
Examination board through which the programme will be considered:
School of Mathematics
Programme specification:
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.
Year1 - View timetable
[Learning Outcomes, Transferable (Key) Skills, Assessment]
Candidates must enrol on exactly 180 or 185 credits overall, with at least 135 credits at level 5M.
Students will be awarded the PGCert if they exit with 60 credits (including 45 at Level 5M), or the PGDip if they exit with 90 credits (including 75 at Level 5M).
Compulsory modules:
Candidates will be required to study the following compulsory modules:
| MATH5825M | Independent Learning and Skills Project | 15 credits | Semester 2 (Jan to Jun) | |
| MATH5835M | Statistical Computing | 15 credits | Semester 1 (Sep to Jan) | |
| MATH5871M | Dissertation in Statistics | 60 credits | 1 Jun to 30 Sep |
Optional modules:
Candidates will be required to study at least 70 credits from the following optional modules:
A "standard" package of module choices will comprise the compulsory modules, together with the following recommended optional modules:
| MATH3714 | Linear Regression and Robustness | 15 credits | Semester 1 (Sep to Jan) | |
| MATH3723 | Statistical Theory | 15 credits | Semester 2 (Jan to Jun) | |
| MATH5772M | Multivariate and Cluster Analysis | 15 credits | Semester 1 (Sep to Jan) | |
| MATH5802M | Time Series and Spectral Analysis | 15 credits | Semester 1 (Sep to Jan) | |
| MATH5824M | Generalised Linear and Additive Models | 15 credits | Semester 2 (Jan to Jun) |
However, depending on the student's background and preferences, any of the above may be replaced by any of the following:
| EPIB3036 | Introduction to Clinical Trials | 15 credits | Semester 2 (Jan to Jun) | |
| EPIB5040M | Introduction to Health Data Science | 15 credits | Semester 1 (Sep to Jan) | |
| EPIB5043M | Further techniques in Health Data Analytics | 15 credits | Semester 1 (Sep to Jan) | |
| EPIB5045M | Modelling Strategies for Causal Inference with Observational Data | 15 credits | Semester 2 (Jan to Jun) | |
| EPIB5046M | Latent Variable Methods | 15 credits | Semester 2 (Jan to Jun) | |
| MATH3565 | Mathematical Biology | 15 credits | Semester 1 (Sep to Jan) | |
| MATH3567 | Evolutionary Modelling | 15 credits | Semester 2 (Jan to Jun) | |
| MATH3734 | Stochastic Calculus for Finance | 15 credits | Semester 2 (Jan to Jun) | |
| MATH3772 | Multivariate Analysis | 10 credits | Semester 1 (Sep to Jan) | |
| MATH3802 | Time Series | 10 credits | Semester 1 (Sep to Jan) | |
| MATH3820 | Bayesian Statistics | 10 credits | Semester 2 (Jan to Jun) | |
| MATH3823 | Generalised Linear Models | 10 credits | Semester 2 (Jan to Jun) | |
| MATH5320M | Discrete Time Finance | 15 credits | Semester 1 (Sep to Jan) | |
| MATH5330M | Continuous Time Finance | 15 credits | Semester 2 (Jan to Jun) | |
| MATH5340M | Risk Management | 15 credits | Semester 2 (Jan to Jun) | |
| MATH5566M | Advanced Mathematical Biology | 20 credits | Semester 1 (Sep to Jan) | |
| MATH5567M | Advanced Evolutionary Modelling | 20 credits | Semester 2 (Jan to Jun) | |
| MATH5714M | Linear Regression, Robustness and Smoothing | 20 credits | Semester 1 (Sep to Jan) | |
| MATH5820M | Bayesian Statistics and Causality | 15 credits | Semester 2 (Jan to Jun) |
Subject to the overall constraint that the student must take at least 135 credits at level 5, and specific constraints related to individual modules (pre-requisites and exclusions, etc).
Elective modules:
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: 30/04/2019
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- Undergraduate module catalogue
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