  Probability models are only useful at explaining the uncertainty of what we
do not know, and should never be used to say what we already know. Probability
and statistical models are useless at discerning cause. Classical statistical
procedures, in both their frequentist and Bayesian implementations are, falsely
imply they can speak about cause. No hypothesis test, or Bayes factor, should
ever be used again. Even assuming we know the cause or partial cause for some
set of observations, reporting via relative risk exagerates the certainty we
have in the future, often by a lot. This over-certainty is made much worse when
parametetric and not predictive methods are used. Unfortunately, predictive
methods are rarely used; and even when they are, cause must still be an
assumption, meaning (again) certainty in our scientific pronouncements is too
high.
