In fitting a straight-line trend by the method of least squares, with \(y\) the actual values and \(y_t\) the trend values, the line is chosen so that
Answer & explanation
Correct answer: option 2
The correct answer is Option (2) → \(\sum (y - y_t)^2\) is least
By the principle of least squares, the best-fitting line is the one for which the sum of the squares of the deviations of the actual values from the trend values is the smallest:
\(\sum (y - y_t)^2\) is least
For this line the sum of the deviations themselves is zero, \(\sum (y - y_t) = 0\), so that sum is not made maximum.