In: Statistics and Probability
Explain what the value of R tells you about the scatterplot. (three or four sentences)
Explain what the value R squared tells you about the model. (three or four sentences)
The correlation r tells the strength of linear association between x and y on the other hand R square when used in the regression model context tells about the amount of variability in y that is explained by the model. In simple regression, R square is literally the square of the correlation between x and y.
R square or Coefficient of determination shows percentage variation in y which is explained by all the x variables together.
Intuitively, when the correlation between x and y is high/ strong the linearity itself lends the model to explain the variation in y more and better. This is the reason we go for models with higher R square. But higher R square may not always be the right thing to go in case of multiple linear regression context
R lies between -1 to 1 but R square or Coefficient of determination lies between 0 and 1