Postgraduate Course: Medical Statistics for the Life Sciences (GMED11027)
Course Outline
| 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. |
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
| Additional Costs | None |
Information for Visiting Students
| Pre-requisites | None |
| Displayed in Visiting Students Prospectus? | No |
Course Delivery Information
|
| Delivery period: 2012/13 Semester 2, Available to all students (SV1)
|
Learn enabled: Yes |
Quota: None |
| Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
| No Classes have been defined for this Course |
| First Class |
First class information not currently available |
| No Exam Information |
Summary of Intended Learning Outcomes
| 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. |
Assessment Information
| 100% project |
Special Arrangements
| None |
Additional Information
| 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 $ú principles and simple 1 & 2 group continuous and categorical examples
4. Hypothesis testing $ú principles and same examples as session 3
5. Correlation and simple linear regression
6. Study design principles $ú randomisation and blocking
7. Study design principles $ú clinical trials and power issues
8. One and Two-way analysis of variance models
9. Method comparison and reproducibility methods
10. Diagnostic testing $ú sensitivity, specificity, PPV, NPV and ROC curves
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| 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.
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| Study Abroad |
Not entered |
| Study Pattern |
10 x 1 hour lectures; 5 x 2 hour practical sessions |
| Keywords | Statistics, clinical trials, experimental design, randomisation, ANOVA, reproducibility, diagnostic |
Contacts
| Course organiser | Dr Niall Anderson
Tel: (0131 6)50 3212
Email: Niall.Anderson@ed.ac.uk |
Course secretary | Ms Margaret Luttrell
Tel: (0131 6)50 3227
Email: Maggie.Luttrell@ed.ac.uk |
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© Copyright 2012 The University of Edinburgh - 31 August 2012 4:04 am
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