Suppose you are reading about a statistically significant result * x* that just reaches a threshold p-value α from a test T+ of the mean of a Normal distribution

*H*_{0}: µ ≤ _{ }0 against *H*_{1}: µ > _{ }0

with *n* iid samples, and (for simplicity) known σ. The test “rejects” *H*_{0 }at this level & infers evidence of a discrepancy in the direction of *H1.*

I have heard some people say:

A. If the test’s power to detect alternative µ’ is very low, then the just statistically significant

isxpoorevidence of a discrepancy (from the null) corresponding to µ’. (i.e., there’s poor evidence that µ > µ’ ). See point* on language in notes.They will generally also hold that if POW(µ’) is reasonably high (at least .5), then the inference to µ > µ’ is warranted, or at least not problematic.

I have heard other people say:

B. If the test’s power to detect alternative µ’ is very low, then the just statistically significant

isxgoodevidence of a discrepancy (from the null) corresponding to µ’ (i.e., there’s good evidence that µ > µ’).They will generally also hold that if POW(µ’) is reasonably high (at least .5), then the inference to µ > µ’ is

unwarranted.

**Which is correct, from the perspective of the frequentist error statistical philosophy?** Continue reading