In regression analysis, if the coefficient of correlation is -1.0, then:
A)the sum of squares for error is -1.0.
B)the sum of squares for regression is 1.0.
C)the sum of squares for error and sum of squares for regression are equal.
D)the sum of squares for regression and total variation in y are equal.

Question

Quizplus · Accepted Answer

A coefficient of correlation of -1.0 indicates a perfect negative linear relationship between the independent and dependent variables. In this case, the sum of squares for regression and total variation in y are equal, as all of the variation in the dependent variable can be explained by the independent variable. The sum of squares for error will be 0, as there is no unexplained variation. Therefore, option D is correct.

In Regression Analysis, If the Coefficient of Correlation Is -1