2019/20 Taught Postgraduate Programme Catalogue
MSc Medical Statistics
|Programme code:||MSC-STAT/MD||UCAS code:|
|Duration:||12 Months||Method of Attendance:||Full Time|
|Programme manager:||Dr Arief Gusnanto||Contact address:||firstname.lastname@example.org|
Total credits: 180
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
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
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).
Students will be required to study the following compulsory modules:
|EPIB3036||Introduction to Clinical Trials||15 credits||Semester 2|
|EPIB5040M||Introduction to Health Data Science||15 credits||Semester 1|
|EPIB5042M||Modelling Prediction and Causality with Observational Data||15 credits||Semester 1|
|MATH5835M||Statistical Computing||15 credits||Semester 1|
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.
|MATH5825M||Independent Learning and Skills Project||15 credits||Semester 2|
|MATH5871M||Dissertation in Statistics||60 credits||1 Jun to 30 Sep|
|EPIB5001M||Research Project||60 credits||1 Oct to 30 Sep|
|EPIB5044M||Professional Skills for Health Data Scientists||15 credits||Semester 2|
|MATH3714||Linear Regression and Robustness||15 credits||Semester 1|
|MATH3723||Statistical Theory||15 credits||Semester 2|
|MATH3772||Multivariate Analysis||10 credits||Semester 1|
|MATH3802||Time Series||10 credits||Semester 1|
|MATH3820||Bayesian Statistics||10 credits||Semester 2|
|MATH3823||Generalised Linear Models||10 credits||Semester 2|
|MATH5714M||Linear Regression, Robustness and Smoothing||20 credits||Semester 1|
|MATH5772M||Multivariate and Cluster Analysis||15 credits||Semester 1|
|MATH5802M||Time Series and Spectral Analysis||15 credits||Semester 1|
|MATH5820M||Bayesian Statistics and Causality||15 credits||Semester 2|
|MATH5824M||Generalised Linear and Additive Models||15 credits||Semester 2|
|EPIB5043M||Further techniques in Health Data Analytics||15 credits||Semester 1|
|EPIB5045M||Modelling Strategies for Causal Inference with Observational Data||15 credits||Semester 2|
|EPIB5046M||Latent Variable Methods||15 credits||Semester 2|
|EPIB5047M||Independent Skills in Health Data Analytics||15 credits||Semester 2|
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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- Undergraduate module catalogue
- Taught Postgraduate module catalogue
- Undergraduate programme catalogue
- Taught Postgraduate programme catalogue
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