Editorial piece in Nature, with an accompanying letter with 800+ signatories adds to the growing number of scientists calling for an end to the misuse of P values and statistical significance to...
Editorial piece in Nature, with an accompanying letter with 800+ signatories adds to the growing number of scientists calling for an end to the misuse of P values and statistical significance to 'prove' results.
vox also has a good supplemental piece about this that also focuses on and explains some of the mechanics behind quantifying statistical significance and p-values in fairly straightforward, more...
vox also has a good supplemental piece about this that also focuses on and explains some of the mechanics behind quantifying statistical significance and p-values in fairly straightforward, more layman's terms.
long overdue. the world is not black and white. everything's on spectra, that require careful consideration. we need to learn to accept uncertainty and nuance, in a world increasingly using black...
long overdue. the world is not black and white. everything's on spectra, that require careful consideration. we need to learn to accept uncertainty and nuance, in a world increasingly using black and white thinking.
"we are not advocating a ban on P values, confidence intervals or other statistical measures — only that we should not treat them categorically... We must learn to embrace uncertainty. One practical way to do so is to rename confidence intervals as ‘compatibility intervals’ and interpret them in a way that avoids overconfidence."
instead of renaming confidence intervals, why not just report sigma values, like physicists already do? that makes it clear significance is on a scale, and challenges readers to make their own judgements
"Third, like the 0.05 threshold from which it came, the default 95% used to compute intervals is itself an arbitrary convention. It is based on the false idea that there is a 95% chance that the computed interval itself contains the true value, coupled with the vague feeling that this is a basis for a confident decision. A different level can be justified, depending on the application."
Editorial piece in Nature, with an accompanying letter with 800+ signatories adds to the growing number of scientists calling for an end to the misuse of P values and statistical significance to 'prove' results.
vox also has a good supplemental piece about this that also focuses on and explains some of the mechanics behind quantifying statistical significance and p-values in fairly straightforward, more layman's terms.
long overdue. the world is not black and white. everything's on spectra, that require careful consideration. we need to learn to accept uncertainty and nuance, in a world increasingly using black and white thinking.
instead of renaming confidence intervals, why not just report sigma values, like physicists already do? that makes it clear significance is on a scale, and challenges readers to make their own judgements