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.
Deze oefening maakt deel uit van de cursus
Introduction to Regression with statsmodels in Python
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# Create the model, fit it
mdl_price_vs_age = ____(____, data=____).____
# Print the parameters of the fitted model
print(____.____)