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> But I think many of the researchers applying it don't either, heh.

As a statistician myself, I'd agree with that statement.

I've actually said previously - and only half-joking - that p-values should be banned from research journals. The problem with p-values is that they don't mean what people generally assume they do, and because they look so close to what people want them to mean ("the probability that my conclusions are wrong, given my assumptions and data"), it's very easy to project spurious meaning onto them.

In reality, p-values actually provide very little information, and the information they do provide is generally not of relevance. But they're so commonly-used that it's very hard to convince people to use more sophisticated techniques for reporting and modeling information.




I guess it won't change until the 'peer-review' process for every article includes a statistician, and papers actually get rejected for improper or insufficient use of statistics.

I think academia these days forces researchers to really care about little except getting grants and getting published (with the former effected by the latter) -- caring about using statistics properly (let alone the actual validity or usefulness of their findings) will hurt rather than help their careers unless it effects one of those two things positively.




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