>Causation without correlation. ...Suppose the value of y is known to be caused by x. The true relationship between x and y is mediated by another factor, call

>Causation without correlation. ...Suppose the value of y is known to be caused by x. The true relationship between x and y is mediated by another factor, call it A, that takes values of +1 or -1 with equal probability. The true process relating x to y is y = Ax. >It is a simple matter to show that the correlation between x and y is zero. Perhaps the most intuitive way is to imagine many samples (observations) of x, y pairs. Over the sub-sample for which the pairs have the same sign (i.e. for which A happened to be +1) y=x and the correlation is 1. Over the sub-sample for which the pairs have the opposite signs (i.e. for which A happened to be -1) y=-x and the correlation is -1. Since A is +1 and -1 with equal probability, the contributions to the total correlation from the two sub-samples cancel, giving a total correlation of zero. It seems to me that this doesn't quite make sense. Sure, the correlation of the average of the numbers is 0, but notice that |x - y| <= |2x|, or that |y| = |x|. That seems like a rather large correlation to me, even though half the time, x and y are positively correlated, and the other half, they're negatively correlated.