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Comment by imjustsaying | Hacker News Reader

I never understood why people took p-values seriously. They never seemed to mean anything of use.

Whenever I brought it up around other academics, no one seemed to want to comment on it. Maybe they were afraid to admit they didn't understand a topic that's apparently important to publishing? Anyone can follow the formula to make a p-value, but there's no requirement to understand its meaning.

I'd love to find their use, but I still haven't found it.

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Before computers could do the complicated math of proper Bayesian updating, it was impossible to get the answer to the question people were asking ("probability of fact given evidence?"), and the science community decided that they'd rather get good answer to bad questions ("probability of evidence given fact?") then bad answers to good questions.

Well, consider the reverse. A 0.05 p-value might mean anything, but what about a 0.5 p-value?

No simple test is going to tell you a hypothesis is definitely correct, but if you can weed out the probably-garbage hypotheses, you can focus on evaluating the remainder more critically.

> there's no requirement to understand its meaning.

This is a feature, not a bug. The fact that the p-value has nothing to do with whether or not the hypothesis is correct is intended to force people to think for themselves rather than using math as a substitute for logic.

If a feature is working in reverse it's probably a bug though- it might be intended to force independent thinking, but in reality all it does is serve as a gameable goalpost, no thought required.

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