Statistics for Health Economics - ECO00052M
Module summary
To introduce you to the foundations of statistical methods for health economics.
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Spring Term 2025-26 |
Module aims
To introduce you to the foundations of statistical methods for health economics.
Module learning outcomes
Upon successful completion of the module you should be able to:
- Explain the basic ideas underlying the theory of probability and classical statistical analysis, including random variables and their probability distributions, descriptive statistics, sampling and sampling error.
- Explain the difference between association and causation and the role played by randomisation in identifying casual effects.
- Take a practical problem and a sample of data, define the problem in a way that is amenable to statistical analysis and explain why the approach adopted is reasonable.
- Perform the relevant computations for the statistical methods covered and be able to provide intuitive explanations of the methods and results, showing how the results are derived.
- Use a software package such as Excel to carry out data management, descriptive statistics and inferential statistics through to multiple regression.
Indicative assessment
| Task | % of module mark |
|---|---|
| Open Exam (2 days) | 100 |
Special assessment rules
None
Indicative reassessment
| Task | % of module mark |
|---|---|
| Open Exam (2 days) | 100 |
Module feedback
Feedback will be given in line with University guidelines
Indicative reading
- Practical Statistics for Medical Research, D. Altman. Chapman and Hall (1991)
- Natural Experiments in the Social Sciences. A Design-Based Approach. T. Dunning. Cambridge (2012).
- Statistics without Tears: A Primer for Non-Mathematicians, D. Rowntree. Penguin Books (2003). St Ives.
- Statistics with confidence, D.G. Altman, D. Machin, T.N. Bryant, M.J. Gardner (eds.) BMJ (2000). London. Second Edition.