In this important paper on the interpretation of statistics in medicine, the authors write:

Blockquote

Misinterpretation and abuse of statistical tests, confidence intervals, and statistical power have been decried for decades, yet remain rampant. A key problem is that there are no interpretations of these concepts that are at once simple, intuitive, correct, and foolproof. Instead, correct use and interpretation of these statistics requires an attention to detail which seems to tax the patience of working scientists. This high cognitive demand has led to an epidemic of shortcut definitions and interpretations that are simply wrong, sometimes disastrously so—and yet these misinterpretations dominate much of the scientific literature.

I was curious if anyone had examples of guidelines that:

- commit one or more of the errors in described in the paper
- have become entrenched in institutional practice due to acceptance by regulatory authorities.

The closest threads that have approached the topic:

**Addendum** A quick search brought up this article by @Stephen, (inspired by @pmbrown just below) which is a good example of what I’m looking for: