Earlier quoted context omitted.
no doubt, the single-disciplinary researchers use bad statistics, too. My broader point is that multidisciplinary researchers are less likely to use statistics correctly, if for no other reason than that the fact that they are multidisciplinary means that they are less likely to be able to handle depth from a personality/self-habits point of view. Perhaps that's a little bit of projection, but I don't use any but the…
It would be interesting to look into this. My experience has been that multi-disciplinary researchers are more likely to be familiar with a broader range of research and familiar with statistical techniques across their different disciplines. Someone with a narrower perspective is more likely to get into bad habits related to their field. I think your comment about them being less likely to be able to handle depth fr…
People seriously just take standard deviations and then plug it into the formula to spit out p values. Without thinking about things like: "should the values be normally distributed? or log-normal?" "How does error propagate through this formula I'm using?" "Is the major source of error in the replicates that I'm using (versus something I might be normalizing to, like a mass measurement)?" "Am I in the linear range of my calibration standards?" "Is using these data quantitatively (versus qualitatively) an honest thing to do?"