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The term "significant" is itself part of the problem. In statistics it is often used to describe an arbitrary threshold where a difference between datasets is a
by pcrh 9y ago
The term "significant" is itself part of the problem. In statistics it is often used to describe an arbitrary threshold where a difference between datasets is assumed to be real. In common parlance this term implies "important" or "meaningful", but the statistical tests are not designed to draw such forward-looking conclusions.
It would be far easier, and more honest, to simply report the P-value obtained by performing a statistical test without adding the term "significant".
- jaggederest 9y agoI'd be interested in a compound metric composed of the likelihood ratio and the p-value. Essentially the more likely your hypothesis, the higher your P value can be, and conversely unlikely hypotheses require stronger evidence. I don't think this solves the problem but maybe it makes that assumption about the hypothesis likelihood more specific.