Module and Programme Catalogue

Search site

Find information on

2017/18 Taught Postgraduate Programme Catalogue

MSc Epidemiology and Biostatistics

Programme code:MSC-EPIB-FTUCAS code:
Duration:12 Months Method of Attendance: Full Time
Programme manager:Dr Richard Feltbower Contact address:r.g.feltbower@leeds.ac.uk

Total credits: 180

Entry requirements:

Academic entry requirements:
Normally a first degree in a science allied with medicine, including biology, ecology, biochemistry, statistics, mathematics, computing, psychology, economics or biomedical science (at least 2:2). We will also consider working experience (two years or more) of research in a quantitative subject area. Non-graduates who have successfully completed three years of a UK medical degree, are normally ranked in the top 50% of the year 3 cohort and wish to take the Epidemiology & Biostatistics course as an intercalated programme will also be accepted.

English language requirements:
- An overall score of 7.0 on IELTS (International English Language Testing System) with at least 6.0 in writing and no other skill below 6.5
- from a TOEFL paper based test the requirement is a minimum score of 600, with 4.5 in the Test of Written English (TWE)
- from a TOEFL computer based test the requirement is a minimum score of 250, with 4.5 TWE
- from a TOEFL Internet based test the requirement is a minimum score of 100, with 25 in the "Writing Skills" score.

School/Unit responsible for the parenting of students and programme:

Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM), School of Medicine

Examination board through which the programme will be considered:

Postgraduate examination board of the School of Medicine

Relevant QAA Subject Benchmark Groups:

Masters degrees are awarded to students who have demonstrated:

i) a systematic understanding of knowledge, and a critical awareness of current problems and/or new insights, much of which is at, or informed by, the forefront of their academic discipline, field of study, or area of professional practice
ii) a comprehensive understanding of techniques applicable to their own research or advanced scholarship
iii) originality in the application of knowledge, together with a practical understanding of how established techniques of research and enquiry are used to create and interpret knowledge in the discipline
iv) conceptual understanding that enables the student to:
- evaluate critically current research and advanced scholarship in the discipline
- evaluate methodologies and develop critiques of them and, where appropriate, to propose new hypotheses.

Typically, holders of the qualification will be able to:
a) deal with complex issues both systematically and creatively, make sound judgements in the absence of complete data, and communicate their conclusions clearly to specialist and non-specialist audiences
b) demonstrate self-direction and originality in tackling and solving problems, and act autonomously in planning and implementing tasks at a professional or equivalent level
c) continue to advance their knowledge and understanding, and to develop new skills to a high level

and will have:
d) the qualities and transferable skills necessary for employment requiring:
- the exercise of initiative and personal responsibility
- decision-making in complex and unpredictable situations
- the independent learning ability required for continuing professional development.

Programme specification:

This revised Masters Programme will make a valuable contribution to the teaching portfolio of the Faculty of Medicine and Health. The programme will produce excellent students wishing to pursue a PhD, and this will improve the Faculty’s ability to recruit excellent PhD students. Increasing the number and quality of PhD students is a major strategic goal of the Faculty, and the LIGHT. The existing MSc in Statistical Epidemiology has delivered graduates have used their enhanced analytical expertise in population health research to bring rigorous methods and new solutions to long-standing analytical questions after: progressing to PhD (n=5); returning to clinical practice (n=2); or securing posts as independent data analysts within academic and applied research institutions (n=3).

Distinctive features include:
1. A focus on statistical methods for observational health and health services research;
2. Extensive links to practice and practice-derived datasets maintained by the LIGHT Data Management Group (including routine health service data);
3. Suitability for graduates with mathematical and/or clinical backgrounds;
4. A balance of semester-long modules providing a sound grounding in fundamental and advanced statistical methods for population health research;
5. Substantial scope for student choice across a range of optional multidisciplinary modules to accommodate different interests and needs;
6. A compulsory generic and transferable skills module to prepare graduates for professional careers as independent researchers;
7. Research projects using clinically-relevant data, supervised by research-active academics and leading to the production of journal papers suitable for publication.
8. The use of blended learning to meet the differing learning styles of individual students, and to provide student paced-learning for those with different aptitudes for mathematical and/or clinical material.

Sustained recruitment to the MSc Epidemiology and Biostatistics indicates that it has established itself as the only advanced training course within the UK specialising in the analysis of observational studies and routine healthcare data tailored to the needs of career enhancers and career changers with either mathematical and/or clinical expertise. In response to growing student demand and the evolving analytical needs of population health, the range of taught modules will be enhanced by introducing additional specialisation in Statistical Epidemiology, Non-Communicable Disease Epidemiology or Applied Population Health through careful guidance in the selection of optional modules.

The formal structures of three large research institutes within the School of Medicine does not reflect any insularity, and the MSc draws on a range of multidisciplinary skills both within and between the School’s three Institutes, including access to optional modules delivered by colleagues based in other Institutes (such as the Genetic Epidemiology module, delivered by colleagues from the Genetic Epidemiology Group within the Leeds Institute of Molecular Medicine (LIMM). The MSc also enjoys cross faculty support from colleagues in the Schools of Geography and Mathematics.


Year1 - View timetable

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

Compulsory modules:

Candidates will be required to study the following compulsory modules:

EPIB5001MResearch Project60 credits1 Oct to 30 Sep (12mth)
EPIB5022MCore Epidemiology15 creditsSemester 1 (Sep to Jan)
EPIB5023MIntroduction to Modelling15 creditsSemester 1 (Sep to Jan)
EPIB5024MStatistical Inference15 creditsSemester 1 (Sep to Jan)
EPIB5030MProfessional Spine15 creditsSemester 2 (Jan to Jun)

Optional modules:

Candidates will be required to study 60 credits from the following optional modules

EPIB3036Introduction to Clinical Trials15 creditsSemester 2 (Jan to Jun)
EPIB5025MMultilevel and Latent variable Modelling15 creditsSemester 2 (Jan to Jun)
EPIB5032MIntroduction to Genetic Epidemiology15 creditsSemester 2 (Jan to Jun)
EPIB5035MNon-communicable Disease Epidemiology15 creditsSemester 2 (Jan to Jun)
EPIB5036MIndependent Learning Skills in Epidemiology and Biostatistics15 creditsSemesters 1 & 2 (Sep to Jun)
EPIB5037MAdvanced Modelling Strategies15 creditsSemester 2 (Jan to Jun)
EPIB5038MAdvanced epidemiological techniques15 creditsSemester 1 (Sep to Jan)
PHLT5110MCommunicable Disease Control and Non-Infectious Environmental Hazards15 creditsSemester 2 (Jan to Jun)
PHLT5125MPopulation Health: Principles and Practice15 creditsSemester 2 (Jan to Jun)

Last updated: 22/09/2017

Disclaimer

Browse Other Catalogues

Errors, omissions, failed links etc should be notified to the Catalogue Team.PROD

© Copyright Leeds 2019