Inverted P-Hacking

A practice where a researcher designs a study or chooses a statistical method specifically to push p‑values as high as possible, usually to support a null hypothesis or to discredit an existing finding. Instead of seeking significance, they seek non‑significance by manipulating sample sizes, outlier removal, or covariate selection. Inverted p‑hacking is common in industry-funded research or ideological debates where the desired outcome is “no evidence of effect.” It operates under the same selective reporting logic as standard p‑hacking but in the opposite direction.

Inverted P-Hacking Example: “The company’s study added a dozen irrelevant variables until the true effect of their pollutant disappeared – inverted p‑hacking, engineering non‑significance.”

Inverted P-Hacking by Dumu The Void April 25, 2026