The difference between the observed points and the regression line points is equal to the correlation.
The strength and direction of a relationship between two or more variables are described by the statistical measure of correlation, which is given as a number. However, a correlation between two variables does not necessarily imply that a change in one variable is the reason for a change in the values of the other.
Regression expresses the relationship as an equation, whereas correlation assesses the strength of the linear link between two variables. The square of the correlation coefficient, also known as Pearson's r, between the observed and predicted values in a regression is sometimes referred to as R2.
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