Cause And Effect: A New Statistical Test That Can Tease Them Apart

Re:Cause And Effect: A New Statistical Test That Can Tease T... by pdabbadabba on Saturday December 20, 2014 @04:51PM (#8778063)

I must say, I do not understand why they have to assume that there is no common cause. What you're looking for is an asymmetry in the the bleeding of noise from one variable into another, right? I.e., if you're hypothesis is that A causes B, then you want to confirm that noise in A also appears in B, but that noise in B does not also appear in A.

The fact that there is a common source of noise in both might make it more difficult to detect this asymmetry (because it weakens your characterization of A or B specific noise) but, on their assumption that noise is typically additive, wouldn't it still be theoretically possible to detect the asymmetry you're looking for? I.e., if A and B have common cause X, then noise from X will appear in A and B, but A noise will not appear in B, and B noise will not appear in A (assuming that A and B also have intrinsic noise sources in addition to the noise they inherit from X). Symmetry is maintained.

What am I not getting?

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Re:Cause And Effect: A New Statistical Test That Can Tease T... by Tycho on Saturday December 20, 2014 @07:17PM (#8778477)

Maybe because you cannot guarantee that noise will bleed?

If you detect bleeding, then great, you have a result.

If you do not detect bleeding, then it could be that there is a confounding variable or it could just be that the noise doesn't bleed. Similarly if there is a confounding variable then you cannot guarantee that the noise will bleed to both sets of observations. You have know way of knowing. Make sense?

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