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Principles of statistics

Module leads

Derrick Bennett Derrick Bennett

Sarah Lewington Sarah Lewington

Sarah Parish Sarah Parish

Jennifer Carter Jennifer Carter

Learning objectives:

  • To understand the underlying principles of medical statistics
  • To gain the technical skills to conduct appropriate statistical analyses independently
  • To produce appropriate publication-quality presentations (figures and tables) of statistical analyses


  1. Introduction to biostatistics and STATA
  2. Data distributions and descriptive statistics
  3. Normal distribution
  4. Prevalence, risks, odds and rates
  5. Hypothesis testing
  6. Studying exposure effects using prevalence, risks, odds and rates
  7. Categorical data
  8. Linear regression I
  9. Linear regression II
  10. Non-parametric methods
  11. Logical regression I
  12. Logical regression II
  13. Logical regression III
  14. Interactions
  15. Modelling strategies for observational studies
  16. Presentation of results I
  17. Statistics module review
  18. Poisson regression
  19. Survival analysis I
  20. Survival analysis II
  21. Survival analysis III
  22. Power and sample size I
  23. Power and sample size II
  24. Attributable fractions
  25. Missing data and multiple imputation
  26. Regression dilution bias
  27. Choosing cut-offs and calculating variance of the log risk
  28. Presentation of results and documentation II
  29. Causal diagrams