Losing symmetry in least squares approximation

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I tried to find the best linear fit to $(1,-1)$, $(-1,1)$, $(-2,-2)$, and $(2,2)$. There is symmetry within the four points: across $y=x$ and $y=-x$. However, the least squares linear approximation for these four points gives a line $y=\frac{3}{5}x$. In this case, the normal equation has a unique solution. This is strange to me in two ways:

  1. Why is this line not symmetric across $y=x$?
  2. Why is $y=\frac{5}{3}x$ not a solution?

I guess this is some artifact of least squares that I have not fully understood. Any help with this matter is greatly appreciated.

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This is because least squares minimizes the sum of squared vertical distances between the actual points and fitted points, i.e. it solves

$$\min_{\alpha,\beta} \sum_i (y_i-\alpha-\beta x_i)^2.$$

Minimizing the squared vertical distances is algebraically convenient and has many useful interpretations (including as a linear projection), which are a subject for another discussion.

Given this understanding, you can intuitively see why your suggested alternative of $y=\frac{5}{3}x $ would not work, as it would result in huge vertical gaps, particularly with the points $(1,-1)$ and $(-1,1)$ .