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Psychology

P-Hacking and the Reproducibility Crisis

Quick fact

A p-value of 0.05 is often taken as evidence of a real effect, but with p-hacking, researchers can inflate the chance of finding a ‘significant’ result to nearly 100% even when no true effect exists. In one famous demonstration, researchers p-hacked a dataset until they obtained a significant correlation between listening to the song ‘When I’m Sixty-Four’ by the Beatles and the participant’s age—a spurious result with no real causal link.

Why this is interesting

A paper with a statistically significant result is often considered a 'finding.' But what if that significance is as fragile as a house of cards? Why can a supposedly rigorous result fail to show up when another lab tries it again?