G Which of the following statements are not true? A. The total sum of squares is the sum of squared deviations about the sample mean of the observed y values. B. The error sum of squares is the sum of squared deviations about the least squares line C. The ratio of the error sum of squares to the total sum of squares is the proportion of total variation that cannot be explained by the simple linear regression model. D. The sum of squared deviations about the least squares regression line is always smaller than the sum of squared deviations about any other line. E. All of the above statements are true.