Answer to Module
1, Exercise 1k:
Error is the sum of the squared deviations of observed scores from the predicted
scores. If SS Error is very small, every observed score is close to the
predicted score, so the plot of every observed score is close to the regression
SS Error is much smaller than SS Total, then the sum of deviations around the
regression line is much smaller than the sum of deviations around the mean.
Thus, the regression equation gives much more accurate predictions of scores
than simply using the mean as the prediction for all scores. The plot would show
a strong linear relationship between X and Y.