i. The coefficient of determination is the proportion of the total variation in the dependent variable Y that is explained or accounted for by its relationship with the independent variable X. ii. The coefficient of determination is found by taking the square root of the coefficient of correlation.
iii. The standard error of estimate measures the accuracy of our prediction.
A) (i), (ii), and (iii) are all correct statements.
B) (i) and (ii) are correct statements but not (iii).
C) (i) and (iii) are correct statements but not (ii).
D) (ii) and (iii) are correct statements but not (i).
E) (i), (ii), and (iii) are all false statements.

Question

Quizplus · Accepted Answer

- The coefficient of determination, often denoted as R^2, indeed explains the proportion of variance in the dependent variable that can be predicted from the independent variable(s), making statement (i) correct.- The coefficient of determination is actually the square of the coefficient of correlation (not the square root), making statement (ii) incorrect.- The standard error of the estimate does measure the standard deviation of the prediction errors (residuals), indicating how accurately the model predicts the dependent variable, which makes statement (iii) correct.

I the Coefficient of Determination Is the Proportion of the Total