7.6 Graphing Residuals From the Model

You might wonder, why are we bothering to generate and save residuals? There are a lot of reasons but one short answer is: it helps us to understand the error around our model, and can suggest ways of improving the model.

Just as the first thing we do when looking at a data set is to examine the distributions of the variables, it is good to get in the habit of examining the distributions of residuals after we fit a new model.

In the following window, we have provided the code to create histograms of Thumb in a facet grid by Gender. Try modifying it to generate histograms of Gender_resid in a facet grid by Gender. Compare the histograms of residuals from the Gender_model with histograms of thumb length.

Here we’ve depicted the histograms of Thumb by Gender (in teal) next to the histograms of Gender_resid by Gender (in darker gray).

The residuals of the Gender_model represent the variation leftover after taking out the part of the variation that can be explained by Gender. The figures below show the mean Thumb length and mean Gender_resid of the two Gender groups.