The coefficient of determination is a distinct output of linear regression analysis. This is usually interpreted as the proportion or fraction of the variance in the dependent variable that can be predicted from the independent variable. This is a measure of how close the data are when fitted in a linear equation or regression line. This is represented by the variable “r^2”.
While the pearson correlation is a direct measure of the closeness and direction of association that occurs between the independent and dependent variable. This is represented by the variable “r”.
As you can see from the variables, we can simply get pearson correlation by taking the square root of the coefficient of determination, hence:
person correlation = sqrt (0.81) = 0.90
