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I'm a grad student in psychology, and as I pursue more and more independent studies in statistics, I am increasingly amazed by the inadequacy of my formal training. Both personal and second hand experience suggests that the paucity of statistical rigor in undergraduate and graduate training is rather ubiquitous within psychology. As such, I thought it would be useful for independent learners like myself to create a list of "Statistical Sins", tabulating statistical practices taught to grad students as standard practice that are in fact either superseded by superior (more powerful, or flexible, or robust, etc.) modern methods or shown to be frankly invalid. Anticipating that other fields might also experience a similar state of affairs, I propose a community wiki where we can collect a list of statistical sins across disciplines. Please, submit one "sin" per answer.

1@whuber There was some good answers, so I've merged them both. – mbq – 2011-02-06T11:02:41.973

I just gave a talk on this subject... A link to the video follows if you are interested. http://www.youtube.com/watch?v=1SNQQvY1ESo&feature=g-upl

– None – 2012-10-21T01:13:53.0571Hi @Amanda, could you give some indication here of what's in the talk? No-one likes the possibility of being rick-rolled. – naught101 – 2012-10-21T02:17:50.833

Applying statistics where it doesn't belong is the main sin. – Aksakal – 2016-08-11T19:19:29.643

5I'm aware that "sin" is possibly inflammatory and that that some aspects of statistical analysis are not black-and-white. My intention is to solicit cases where a given commonly-taught practice is pretty clearly inappropriate. – Mike Lawrence – 2010-11-15T18:53:14.270

5You can also add biology/life sciences students to the mix if you like ;) – nico – 2010-11-15T19:03:17.187

1maybe retitle it life science statistical sins?... or something else more specific... – John – 2010-11-15T19:27:28.377