Linear regression with a categorical explanatory variable
Great job calculating those grouped means! As mentioned in the last video, the means of each category will also be the coefficients of a linear regression model with one categorical variable. You'll prove that in this exercise.
To run a linear regression model with categorical explanatory variables, you can use the same code as with numeric explanatory variables. The coefficients returned by the model are different, however. Here you'll run a linear regression on the Taiwan real estate dataset.
taiwan_real_estate is available and the ols() function is also loaded.
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.
# Create the model, fit it
mdl_price_vs_age = ____(____, data=____).____
# Print the parameters of the fitted model
print(____.____)