Reference Collection to push back against "Common Statistical Myths"

[R_cubed]

@EpiLearneR You might find this open access paper valuable:

Statistical tests, P values, confidence intervals, and power: a guide to...

Search for @Sander (Sander Greenland) here, and you will find a lot of excellent papers on these misinterpretations as well as corrective measures. If you read them slowly and are prepared to look up the mathematics you do not know, they will teach you a lot.

Here is a good link to some of the things he has written on this:

Predicting survival of cancer patients using the horoscope: astrology, causal inference, seasonality, frequentist & Bayesian approach

Answering that gets into a big topic area… Various transforms of the observed P-value p such as 1−p, 1/p, and log(1/p) have been used as measures of evidence against statistical models or hypotheses (which are parts of models). Part of the interpretation problem is that those statistical models get confused with the theories that predict them. Correct understanding however requires keeping them distinct, because the measures refer only to the statistical model used to derive the p-value; purely…