Model Averaging Basics

Welcome – it’s great to see you here! This course has 9 components:

  • Preliminaries – the benefits of averaging and using weighted averages
  • Model evaluation and parsimony – what constitutes a ‘good’ model? Exploring the trade-off between model complexity and model utility
  • An introduction to Information Theory – the concept of entropy
  • Kullback-Leibler Information
  • Akaike Information Criterion (AIC)
  • Interpretation and use of the AIC
  • Corrected
  • Akaike Information Criterion (AICc)
  • (Frequentist) Model averaging
  • Quiz

At the end of the course there is a short quiz.

Click here to start your lesson.

Coming soon ...