I the Least Squares Technique Minimizes the Sum of the Squares

i. The least squares technique minimizes the sum of the squares of the vertical distances between
The actual Y values and the predicted values of Y.
ii. When a regression line has a zero slope, indicating a lack of a relationship, the line is vertical to
The x-axis.
iii. In regression analysis, the predicted value of Y' rarely agrees exactly with the actual Y value, i.e.,
We expect some prediction error.

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.