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Principles of statistics 1

Module leads

Derrick BennettDerrick Bennett

 Sarah ParishSarah Parish

Jennifer CarterJennifer Carter

 Sofia MassaSophia Massa

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

Sessions:

  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. Standardisation
  9. Linear regression I
  10. Linear regression II
  11. Non-parametric methods
  12. Logistic regression I
  13. Logistic regression II
  14. Logistic regression III
  15. Interactions
  16. Modelling strategies for observational studies
  17. Presentation of results I
  18. Statistics module review
  19. Poisson regression
  20. Survival analysis I
  21. Survival analysis II
  22. Survival analysis III
  23. Choosing cut-offs and variance of the log risk
  24. Presentation of results and documentation II
  25. Regression dilution bias
  26. Power and sample size I
  27. Power and sample size II
  28. Attributable fractions
  29. Missing data and multiple imputation