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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

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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(____.____)
Edit and Run Code