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Exercise

Distribution of outcome variable values

Stratifying by the outcome variable when generating training and test datasets ensures that the outcome variable values have a similar range in both datasets.

Since the original data is split at random, stratification avoids placing all the expensive homes in home_sales into the test dataset, for example. In this case, your model would most likely perform poorly because it was trained on less expensive homes.

In this exercise, you will calculate summary statistics for the selling_price variable in the training and test datasets. The home_training and home_test tibbles have been loaded from the previous exercise.

Instructions 1/2

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  • 1
    • Calculate the minimum, maximum, mean, and standard deviation of the selling_price variable in home_training.
  • 2
    • Calculate the minimum, maximum, mean, and standard deviation of the selling_price variable in home_test.