3. The least-squares line for predicting y from x is not the same line as the least-squares line for predicting x from y. The least-squares line is, by definition, the line that has the smallest possible sum of squared deviations of points from the line in the y direction

(it minimizes os y 2y⁄

d2). The line that minimizes the sum of squared deviations in the y direction is not generally the same as the line that minimizes the sum of the squared deviations in the x direction. So, for example, it is not appropriate to fit a line to data using y 5 house price and x 5 house size and then use the resulting leastsquares line Price 5 a 1 b(Size) to predict the size of a house by substituting in a price and then solving for size. Make sure that the dependent and independent variables are clearly identified and that the appropriate line is fit.