Least Squares Approximation - Maple Help

 Main Concept The least-squares approximation to a set of data points  is the line $y=a\cdot x+b$ that comes closest to going through all the points, in the following sense:   The sum of the squares of all the errors (the difference in the y-value between the data point and the closest point on the line) is minimized.   The problem is to find values $a$ and $b$ such that the sum  is minimal.