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The conventional practice of rejecting the null hypothesis when $$p < 0.05$$ is criticized for creating a mathematically arbitrary dividing line. This rigid threshold can lead to nearly identical findings—such as one study with $$p = 0.04$$ and another with $$p = 0.06$$—being treated as fundamentally different, with only the former deemed worthy of publication.

Arbitrary Nature of the 0.05 Significance Threshold

The rigid convention of statistical significance contributes to the 'file drawer problem,' where high-quality research that does not reach the $$p < 0.05$$ threshold remains unpublished. Because journals prioritize significant results, many studies with similar effect sizes are excluded from the scientific literature simply because they fell on the wrong side of an arbitrary threshold.

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