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you have to bend the truth because it would not work otherwise at all. Your distribution is not normal - it almost never is, now you have to argue that the met
by glofish 7y ago
you have to bend the truth because it would not work otherwise at all.
Your distribution is not normal - it almost never is, now you have to argue that the method is still robust - there is no proof that is indeed robust as you claim. Then your measurement is a bit biased, see on Tuesdays the measurements do turn out a little bit differently, but most often does not matter, so you skimp over that as well.
Statistics is the wrong approach because if you did everything correctly and stuck to the letter of it you only end up hurting yourself. You'll make fewer of the valid discoveries that you make when you bend it a bit.
This is the fundamentally wrong thing about it! Strictly sticking to the rules will make you weaker. Bending statistics a little leads to more valid results.
- lotsofpulp 7y agoI don’t understand. Using statistics doesn’t imply using normal distributions.
- glofish 7y agoI just gave you an example, there are many statistical measures that have that particular requirement. If it is not normality then something else. Every statistical measure makes assumptions, most of which never quite hold true. That was my point. When someone uses statistics they always fudge things a bit. Many times does not matter, if you were stickler for "precision" it would not work.