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.

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?

Exercise

Correlation and R-squared

Instructions