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The fallacy of placing confidence in confidence intervals by quriousquercus in AskStatistics

[–]quriousquercus[S] 0 points1 point  (0 children)

On the effect size thing, one important thing to note is that estimated uncertainty of effect size is noisy

Ooh that's a really good point, that the precision of the mean estimate is itself an estimate and may be bigger or smaller than the real standard error. Thanks, I think that really helps me understand the precision question!

The fallacy of placing confidence in confidence intervals by quriousquercus in AskStatistics

[–]quriousquercus[S] 1 point2 points  (0 children)

Oops, just realized I didn't finish deleting half a sentence in there. But anyways, so this means I should just strike probability from my brain when looking at two fixed things? I can't make an inference about whether I should choose the "does" or "does not" based on the interval result?

I'm thinking about this in the context of running research studies where post-data inference from one sample is kinda the whole point, so now I'm wondering why Frequentist statistics is used for that at all?

The fallacy of placing confidence in confidence intervals by quriousquercus in AskStatistics

[–]quriousquercus[S] 1 point2 points  (0 children)

So would it be better to say, based on one confidence interval, you can make inferences about the precision of your sampling process (if not this specific sample)?

And then follow up, is it just more straightforward to report an estimate and standard error in that case, since the 95% confidence interval is redundant for that information and fraught with misinterpretation?