Answer:
The coefficient of determination is used to measure how well a model fits the real data, or how well it can replicate them. The closer to 1 the value of R ^ 2 the more accurate the model is.
In this case, that R ^ 2 = 0.661 means that the model fits moderately to the variable to be studied.
For a linear regression model, the coefficient of determination is the square of the correlation coefficient r of Pearson. So:
[tex]r =\sqrt{R^2}[/tex]
r = 0.813
This value of r close to 1 means that the length of the essays sent to a teacher (x) and the score that the teacher gave to the essay (and) are highly related.
