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Exercise

Correlation and R-squared

The linear correlation of two variables, \(x\) and \(y\), measures the strength of the linear relationship between them. When \(x\) and \(y\) are respectively:

  • the outcomes of a regression model that minimizes squared-error (like linear regression) and
  • the true outcomes of the training data,

then the square of the correlation is the same as \(R^2\). You will verify that in this exercise.

unemployment and unemployment_model are available for you to use.

Instructions
100 XP
  • Use cor() to get the correlation between the predictions and female unemployment. Assign it to the variable rho and print it. Make sure you use Pearson correlation (the default).
  • Square rho and assign it to rho2. Print it.
  • Compare rho2 to \(R^2\) from the model (using glance()). Is it the same?
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