# DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014 Archive for reference only THIS PAGE IS OUT OF DATE

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# Postgraduate Course: Medical Statistics for the Life Sciences (GMED11027)

 School School of Clinical Sciences College College of Medicine and Veterinary Medicine Course type Standard Availability Available to all students Credit level (Normal year taken) SCQF Level 11 (Postgraduate) Credits 10 Home subject area General Courses (Medicine) Other subject area None Course website None Taught in Gaelic? No Course description This course provides an introduction to key concepts and topics in the statistical methods typically used in biomedical sciences, with particular attention to the principles of good experimental design and appropriate methods of analysis. It will also provide some training in practical data analysis using specialist statistical software.
 Pre-requisites Co-requisites Prohibited Combinations Other requirements None Additional Costs None
 Pre-requisites None Displayed in Visiting Students Prospectus? No
 Not being delivered
 Students should be familiar with the basic principles underlying statistical thinking, including topics such as types of data, the relationship of population to sample, sampling methods, confidence intervals, hypothesis testing and experimental design and randomisation. They should understand and be able to apply simple one and two-group parametric tests, correlation coefficients, simple linear regression models, and simple fixed-effect analysis of variance models. They should be able to analyse correctly method comparison and reproducibility studies and use the appropriate quantities to measure performance of diagnostic and prognostic tests. They should develop competence in implementing the above methods in statistical software.
 100% project
 None
 Academic description Not entered Syllabus 1. Introduction to principles of statistical inference, types of data and graphical and simple summary measures 2. Basic probability and probability distributions 3. Confidence intervals ¿ principles and simple 1 & 2 group continuous and categorical examples 4. Hypothesis testing ¿ principles and same examples as session 3 5. Correlation and simple linear regression 6. Study design principles ¿ randomisation and blocking 7. Study design principles ¿ clinical trials and power issues 8. One and Two-way analysis of variance models 9. Method comparison and reproducibility methods 10. Diagnostic testing ¿ sensitivity, specificity, PPV, NPV and ROC curves Transferable skills Not entered Reading list 1. Statistics at Square One, Ninth Edition (1997). Swinscow, TDJ. BMJ (Download at http://www.bmj.com/statsbk/) 2. Medical Statistics at a Glance (2000). Petrie, A and Sabin, C. Blackwell. 3. Practical Statistics for Medical Research (1991) Altman, D.G. Chapman and Hall/ CRC. Study Abroad Not entered Study Pattern 10 x 1 hour lectures; 10 x 1 hour practical sessions Keywords Statistics, clinical trials, experimental design, randomisation, ANOVA, reproducibility, diagnostic
 Course organiser Dr Niall Anderson Tel: (0131 6)50 3212 Email: Niall.Anderson@ed.ac.uk Course secretary Ms Margaret Luttrell-Outsios Tel: (0131 6)50 3227 Email: Maggie.Luttrell@ed.ac.uk
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