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Exercise

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 just 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.

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  • Run and fit a linear regression with price_twd_msq as the response variable, house_age_years as the explanatory variable, and taiwan_real_estate as the dataset. Assign to mdl_price_vs_age.
  • Print its parameters.