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2019/20 Taught Postgraduate Programme Catalogue

MSc Medical Statistics

Programme code:MSC-STAT/MDUCAS code:
Duration:12 Months Method of Attendance: Full Time
Programme manager:Dr Arief Gusnanto Contact

Total credits: 180

Entry requirements:

2:1 in a first degree with a substantial statistical and mathematical component.

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:

At the end of the programme, students should:
- appreciate theoretical and practical perspectives on issues in medical statistics;
- be able to select and apply appropriate statistical methods for the analysis of medical data, using suitably chosen software packages;
- be prepared to embark on a programme of research as a research student or a career as a medical statistician;
- be able to explain statistical methods and results of statistical analysis in both written and verbal form, to both technical and non-technical audiences;
- have undertaken a substantial statistical project under supervision.

Year1 - View timetable

[Learning Outcomes, Transferable (Key) Skills, Assessment]

Students 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:

Students will be required to study the following compulsory modules:

EPIB3036Introduction to Clinical Trials15 creditsSemester 2
EPIB5040MIntroduction to Health Data Science15 creditsSemester 1
EPIB5042MModelling Prediction and Causality with Observational Data15 creditsSemester 1
MATH5835MStatistical Computing15 creditsSemester 1

Optional modules:

Students must take both modules from either List A or List B.

They are also required to study at least 25 credits from Lists C and D including at least one module from List C.


MATH5825MIndependent Learning and Skills Project15 creditsSemester 2
MATH5871MDissertation in Statistics60 credits1 Jun to 30 Sep


EPIB5001MResearch Project60 credits1 Oct to 30 Sep
EPIB5044MProfessional Skills for Health Data Scientists15 creditsSemester 2


MATH3714Linear Regression and Robustness15 creditsSemester 1
MATH3723Statistical Theory15 creditsSemester 2
MATH3772Multivariate Analysis10 creditsSemester 1
MATH3802Time Series10 creditsSemester 1
MATH3820Bayesian Statistics10 creditsSemester 2
MATH3823Generalised Linear Models10 creditsSemester 2
MATH5714MLinear Regression, Robustness and Smoothing20 creditsSemester 1
MATH5772MMultivariate and Cluster Analysis15 creditsSemester 1
MATH5802MTime Series and Spectral Analysis15 creditsSemester 1
MATH5820MBayesian Statistics and Causality15 creditsSemester 2
MATH5824MGeneralised Linear and Additive Models15 creditsSemester 2


EPIB5043MFurther techniques in Health Data Analytics15 creditsSemester 1
EPIB5045MModelling Strategies for Causal Inference with Observational Data15 creditsSemester 2
EPIB5046MLatent Variable Methods15 creditsSemester 2
EPIB5047MIndependent Skills in Health Data Analytics15 creditsSemester 2

Elective modules:

Student may choose 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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