[soldeace]

Once I had an argument with a PhD biologist at my university because she was doing a Fisher's exact test in the most insane way I had ever seen: taking floating point ratios instead of integers, and because the stats program she used didn't take floating points as valid inputs for the test---obviously---, her workaround was to multiply these numbers by 100 to get integers. She refused to back down on this madness because "her supervisor did it like this, and his supervisor before him". In the end, her paper was peer reviewed and published and it was the first in a series of let downs that made me decide not to pursue a career in academia. Sometimes it's not like researchers want to tamper with their results. It's just that statistical ignorance is widespread and affect even the reviewers that were supposed to be the first line of defense. Which is a huge problem for an environment that relies too much on p-values and not so much on explaining them.