So continuing on from last time’s analysis which we used to introudce one new extra variable to a model and we tried to check how it affected the fit and we can do so by analysing it’s underlying characteristic graphs.
We look at the residuals vs fitted curves first to check for heteroskedasticity and we can check that by the balloning of the values at the end.
In the below grah we see the QQ plots of the normalized behavior and we don’t see anything largely out of the ordinary here as we did with the heteroskedastic nature of the residuals vs fitted graph.
We see more of the same heteroskedastic nature from the standardized nature of the residuals plotted against the fitted values of the model.
We take a look at the residuals vs leverage graph to check how the outlier values are affeccting any chances of making a good read in the final model but we do not see any such behavior on a large scale here in the below graph.
