The method of least squares dictates that we choose a regression line where the sum of the square of deviations of the points from the line is:

A. The central limit theorem B. The law of statistical regularly C. The law of inertia of large numbers D. None of the above

A. Sampling error B. Measurement error C. Coverage error D. Non-response error

A. Both (A) and (R) are true B. (A) is true, but (R) is false C. (A) is false, but (R) is true D. Both (A) and (R) are false

A. 0 B. 1 C. 0.4 D. 0.8