Interactions with understandable coeffs
The previous model with the interaction term returned coefficients that were a little tricky to interpret. In order clarify what the model is predicting, you can reformulate the model in a way that returns understandable coefficients. For further clarity, you can compare the results to the models on the separate house age categories (mdl_0_to_15, mdl_15_to_30, and mdl_30_to_45).
taiwan_real_estate, mdl_0_to_15, mdl_15_to_30, and mdl_30_to_45 are available.
This exercise is part of the course
Intermediate Regression with statsmodels in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Model price vs. house age plus an interaction, no intercept
mdl_readable_inter = ____
# Print the coefficients for mdl_0_to_15
print("mdl_0_to_15 coefficients:", "\n", ____)
# Print the coefficients for mdl_15_to_30
print("mdl_15_to_30 coefficients:", "\n", ____)
# Print the coefficients for mdl_30_to_45
print("mdl_30_to_45 coefficients:", "\n", ____)
# Print the coefficients for mdl_readable_inter
print("\n", "mdl_readable_inter coefficients:", "\n", mdl_readable_inter.params)