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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 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.
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