Least-Squares fit for a line Concept

AI Thread Summary
The least-squares fit for a line through a set of points always intersects at the average coordinates, known as the "center of gravity" (x-bar, y-bar). This relationship is derived from the equations for coefficients A and B, which are calculated using sums of the x and y values. The equations demonstrate that the averages influence the line's slope and intercept. The solution hinges on understanding how these averages relate to the overall distribution of the data points. The discussion emphasizes the importance of these mathematical relationships in deriving the least-squares fit.
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Homework Statement



Prove the following useful fact: the least-squares fit for a line through any set of points (x_1,y_1) ...,(x_N, y_N) always passes through the "center of gravity" (x-bar, y-bar) of the points, where the bar denotes the average of the N values concerned. [Hint: you know that A and B satisfy the equation:
AN + B(sigma)x_i = (sigma)y_i ]


Homework Equations



A(sigma)x_i + B(sigma) x_i^2 = (sigma) x_i*y_i

A = [(sigma)x^2(sigma)y - (sigma)x(sigma)xy]/ [N(sigma)x^2 - ((sigma)x)^2]

B = [N(sigma)xy - (sigma)x(sigma)y]/ [N(sigma)x^2 - ((sigma)x)^2]


The Attempt at a Solution



I think the solution has to do with the solved equations for A and B and their relation to dividing by N, the number of values concerned, which eventually yields the "center of gravity," that is (x-bar, y-bar). I'd appreciate any help. Thanks in advance! :smile:
 
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