(Bayesian) Informative Hypothesis Evaluation (e-learning)

In this e-learning course (with content for one-day which can be spread out over four days), participants will be introduced to informative hypotheses, which are alternatives for the traditional null and alternative hypotheses, and to the AIC-type criterion GORIC(A) and the Bayes factor, which are alternatives for the p-value.

PhD students, (junior) lecturers and researchers working at a university.

For an overview of all our Winter school courses offered by the Department of Methodology and Statistics please click here

Introduction to (Bayesian) informative hypothesis evaluation using JASP and/or R.

Learning goals of this course

After following this course,

you have some background knowledge of model selection techniques; you are able to:

• think outside of the null-hypothesis box;

• evaluate informative hypothesis using JASP and/or R;

• interpret the JASP and/or R output.