The Akaike information criterion (AIC) is an estimator of prediction error and thereby relative quality of statistical models for a given set of data.Given a collection of models for the data, AIC estimates the quality of each model, relative to each of the other models. Thus, AIC provides a means for model selection. If you want to know more AIC, sign up now!

By completing this course, you will be able to develop a better understanding of how AIC works with mixed models and integrated models.