The explanation of p-value in this article isn’t quite right. If we assume there is no _actual_ difference between two groups, the p-value tells us the probability that the _observed_ difference (or larger) is due to random chance. By convention, we reject this hypothesis of no
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difference if p-value is below a cutoff, for example, 0.05. P-hacking is doing whatever it takes to wring p-values < 0.05 from data, which as the article notes, is a big no-no that leads to wrong conclusions.
End of conversation
New conversation -
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“science”
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The Replication Crisis is real.
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