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>"I’ve come to think that the most fundamental problem with p-values is that no one can really say what they are." Not surprising. The correct interpretation o
by nonbel 11y ago
>"I’ve come to think that the most fundamental problem with p-values is that no one can really say what they are."
Not surprising. The correct interpretation of p-values was not discovered until ~2 years ago. If you search around the internet you will find out that, according to the discoverer, he couldn't find a stats journal to publish it. The number of people who know the correct definition must be vanishingly small.
Thank god for arxiv, or I would have never understood p-values:
http://arxiv.org/abs/1311.0081 http://arxiv.org/abs/1311.0081
tldr: Calculating the p-value + sample size is a lossless compression algorithm. The thing being compressed is a likelihood function (way of describing effect size).
- kgwgk 11y agoI think you overestimate the importance of that paper. You can get "a" likelihood from the p-value in the same way that a sufficient statistic determines "the" likelihood function. In the best case, if the sufficient statistic is one-dimensional and you are doing a one-tailed test, both likelihood functions are the same (because the mapping from the sufficient statistic to the p-value is bijective). In general you're losing information (there will be multiple values of the sufficient statistic mapped to the same p-value).