What can be said about R² when a linear regression results in an ANOVA table with a large total sum of squares and a relatively small model sum of squares? A) R² will be small because the explanatory variable explains a small portion of the variability in the outcome. B) R² will be large because the model explains most of the variability in the outcome. C) R² will be small because the model explains a small portion of the variability in the explanatory variable. D) R² will not be affected because it does not involve the model sums of squares or the total sums of squares.

Question

Quizplus · Accepted Answer

The R² is calculated by dividing the model sums of squares by the total sum of squares. This will cause the R² to be small.

What Can Be Said About R² When a Linear Regression