Beyond null-hypothesis testing: Transparent and informative methods in three statistical frameworks
This 3-day course teaches skills for informative and transparent evaluation of theory-based hypotheses using p-values, information criteria, and Bayes factors. Participants will learn to apply open-science principles and cutting-edge statistical techniques that ensure maximally informative analyses. Contemporary issues - such as publication bias, questionable research practices, the statistical evaluation of (non-null) hypotheses, and methods for evaluating the same research question with multiple (replication) studies - are also addressed. The course will be non-technical in nature and is targeted at PhD students and researchers who want to apply the presented approaches to their own data.