Residual standard error
Residual standard error (RSE) is a measure of the typical size of the residuals. Equivalently, it's a measure of how wrong you can expect predictions to be. Smaller numbers are better, with zero being a perfect fit to the data.
Again, you'll look at the models from the advertising pipeline, mdl_click_vs_impression_orig and mdl_click_vs_impression_trans.
This exercise is part of the course
Introduction to Regression with statsmodels in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Calculate mse_orig for mdl_click_vs_impression_orig
mse_orig = ____
# Calculate rse_orig for mdl_click_vs_impression_orig and print it
rse_orig = ____
print("RSE of original model: ", rse_orig)
# Calculate mse_trans for mdl_click_vs_impression_trans
mse_trans = ____
# Calculate rse_trans for mdl_click_vs_impression_trans and print it
rse_trans = ____
print("RSE of transformed model: ", rse_trans)