Become more confident when discussing with leading healthcare providers about clinical results. This course covers key biostatistical concepts required to review and interpret findings published in the medical literature. Selected scientific publications are reviewed, discussed and criticised in terms of bias, uncertainty and scope.
- Introduction to statistics: Population vs. sample, variability, role of statistics in scientific research
- Notion of variables: outcomes, factors, covariates, confounders, etc.
- Key elements in descriptive statistics: Mean, median, standard deviation, standard error, etc.
- Principle of statistical inference: notion of risk, significance level, p-value, power of a study, confidence intervals
- Use of statistical inference in equivalence, non-inferiority and superiority studies
- Common statistical issues in medical research: sample size calculation, dealing with multiple testing
- Overview of commonly used techniques in medical research: this part is customised according to the course length and the methods used in the selected papers. It focuses on the principle of each method, data it can handle, results it provides, its scope and limitations
- Overview of meta-analysis
- The jargon used in biostatistics
- The statistical principles of scientific research
- What drives the choice of a statistical method
- How to criticise scientific papers and to assess the quality of the results and the scope of the conclusions
Recommended Duration: 1 day(s)