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Just a note

It is often assumed, quite wrongly, that the difference between a treatment and an observation is that treatments are free from error but observations are not. Indeed many statistical analyses assume just that.

Observing that variable A and variable B are correlated (or associated) at very best might suggest that A caused B, or B caused A! All too often the variation you observe in A and B both result from some (unobserved) variable C.

In contrast, if you apply treatment X then observe Y, it is much easier to argue that X really did cause Y - even if you do not know the exact value of X that you applied.