Bayesian Statistics, Miscellaneous Statistics

How best to partition data into test and holdout samples?

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Bill Harris writes: In “Type M error can explain Weisburd’s Paradox,” you reference Button et al. 2013. While reading that article, I noticed figure 1 and the associated text describing the 50% probability of failing to detect a significant result with a replication of the same size as the original test that was just significant. At that point, something clicked:…
Original Post: How best to partition data into test and holdout samples?

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