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It isn't so much that there is no "truthful link", it is that everything is linked to everything else to some degree and the mathematical models they use for the null hypothesis are just "defaults". These assumptions are almost always violated. The statistical tests detect that, and are providing "true positives".



Yes, this is kind of exactly the attitude change I am talking about.

The “true positives” found in your model can be expected to have no predictive value, so what is the point of identifying these?




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