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2019/20 Taught Postgraduate Programme Catalogue

MSc Statistics

Programme code:MSC-STATUCAS 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:

MATH5825MIndependent Learning and Skills Project15 creditsSemester 2
MATH5835MStatistical Computing15 creditsSemester 1
MATH5871MDissertation in Statistics60 credits1 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:

MATH3714Linear Regression and Robustness15 creditsSemester 1
MATH3723Statistical Theory15 creditsSemester 2
MATH5772MMultivariate and Cluster Analysis15 creditsSemester 1
MATH5802MTime Series and Spectral Analysis15 creditsSemester 1
MATH5824MGeneralised Linear and Additive Models15 creditsSemester 2

However, depending on the student's background and preferences, any of the above may be replaced by any of the following:

EPIB3036Introduction to Clinical Trials15 creditsSemester 2
EPIB5040MIntroduction to Health Data Science15 creditsSemester 1
EPIB5043MFurther techniques in Health Data Analytics15 creditsSemester 1
EPIB5045MModelling Strategies for Causal Inference with Observational Data15 creditsSemester 2
EPIB5046MLatent Variable Methods15 creditsSemester 2
MATH3565Mathematical Biology15 creditsSemester 1
MATH3567Evolutionary Modelling15 creditsSemester 2
MATH3734Stochastic Calculus for Finance15 creditsSemester 2
MATH3772Multivariate Analysis10 creditsSemester 1
MATH3802Time Series10 creditsSemester 1
MATH3820Bayesian Statistics10 creditsSemester 2
MATH3823Generalised Linear Models10 creditsSemester 2
MATH5320MDiscrete Time Finance15 creditsSemester 1
MATH5330MContinuous Time Finance15 creditsSemester 2
MATH5340MRisk Management15 creditsSemester 2
MATH5566MAdvanced Mathematical Biology20 creditsSemester 1
MATH5567MAdvanced Evolutionary Modelling20 creditsSemester 2
MATH5714MLinear Regression, Robustness and Smoothing20 creditsSemester 1
MATH5820MBayesian Statistics and Causality15 creditsSemester 2

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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