From Nature, we learn that in statistics, P values problems are just the tip of the iceberg:
P values are an easy target: being widely used, they are widely abused. But, in practice, deregulating statistical significance opens the door to even more ways to game statistics — intentionally or unintentionally — to get a result. Replacing P values with Bayes factors or another statistic is ultimately about choosing a different trade-off of true positives and false positives. Arguing about the P value is like focusing on a single misspelling, rather than on the faulty logic of a sentence.
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The ultimate goal is evidence-based data analysis. This is analogous to evidence-based medicine, in which physicians are encouraged to use only treatments for which efficacy has been proved in controlled trials. Statisticians and the people they teach and collaborate with need to stop arguing about P values, and prevent the rest of the iceberg from sinking science.
Suppose “evidence-based data analysis” catches on? How will Darwinism fare? How will ID fare?
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