Question

A famous statistician asserted that it is very useful to use both the coefficients of determination and nondetermination when explaining the strength of correlations to non-statisticians. Why do you think she said this?

Answer 1

The coefficient of determination is the square of the correlation coefficient (r²).

It is the measure of the proportion of the variation of one of the correlated variables, explainable by the

variation of the other variable. So using the coefficient of determination we can understand the explanation power of the regression equation. But we don't know the unexplained power of the model.

The coefficient of nonderermination represents that the part of the dependent variable's total variation

not accounted for by linear association with the independent variable. So that using this coefficient we can understand the unexplained percentage of the model.

Therefore both the coefficient are usefull for the non-statisticians.