Power analysis

Reflections on the power and sample size of your study are essential to allow adequate inferential conclusions about your research hypotheses, both when designing your study and when interpreting the results. This course provides a gentle, non-technical introduction to the concept of statistical power and how this is influenced by sample size – among other factors, as well as a practical introduction to running your own power calculations in R, G*Power and SPSS for common statistical analyses such as t-tests and linear regression. We will also discuss the difference between significance and relevance, how power and effect size come into play during statistical tests and how p-values might be misleading as a standalone criterion for your hypotheses.

Note that this course is currently in a pilot stage and is currently offered in a one-day format with the intention to offer a more elaborate version at the beginning of the next academic year. While all the aforementioned topics will be present in this pilot session, we are open to expand this course based on your feedback and needs.