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here's the issue: assume that, to simplify, that every research paper out of there has findings with p-value < 0.05 - that means one in 20 papers has wrong con
by LoSboccacc 9y ago
here's the issue:
assume that, to simplify, that every research paper out of there has findings with p-value < 0.05 - that means one in 20 papers has wrong conclusions in it.
or that one in 20 teams will not be able to reproduce findings.
0.05 is just removed enough from coincidence that, given a solid theory, corroborates the findings. but running across data to find correlation and using 0.05 as threshold is a surefire way to find something that has no actual significance beyond mathematics and zero ground in reality.
- deleted 9y ago[deleted]
- hedora 9y agoBecause of conditional probabilities, your analysis is wrong. This xkcd explains the issue. Someone else linked to it already, but it exactly describes the problem -- with p=0.05 >> 5% of published results are incorrect: https://xkcd.com/882/ https://xkcd.com/882/
- vacri 9y agoYou're making the same mistake in reverse. The p-value is not a marker of correctness, but of confidence. If something doesn't reach the p-value cutoff, that doesn't mean that the effect doesn't exist, just that it didn't meet the confidence level. A paper could be entirely correct in its hypothesis, yet not meet the confidence level in its experimentation.