See module specification for other years:
2022-232023-24
Module summary
To introduce you to the foundations of statistical methods for health economics.
Module will run
Occurrence
Teaching period
A
Spring Term 2024-25
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.