4 ms·
this is not the only reason 'why'. Another persistent reason is the function of the alpha value in typical null hypothesis testing leading to the (misguided) id
by begemotz 3y ago
this is not the only reason 'why'. Another persistent reason is the function of the alpha value in typical null hypothesis testing leading to the (misguided) idea that a p value of .04 is functionally equivalent to a p value of 2.3e-10 since both are below threshold.
So i would argue that this is more damning - essentially a misunderstanding of probability and what p values tell us at a fundamental level.
- jampekka 3y agoTypically you see p < 0.01 etc even with 0.05 alpha. A lot of stats software gives only those inexact values. But yes, the interpretation of p-values and confidence levels are wildly misunderstood. p > alpha is often taken as "evidence of absence" of an effect, which is just wrong. Or when for some quantity p1 < alpha and other p2 > alpha, it's often intepreted that the quantities differ. It's a mess.