Statistical Significance Threshold

Statistical significance threshold is the cutoff used in Don’t hate the replicator, hate the game to explain why some results become publishable and others do not. The episode uses the conventional 5 percent threshold as the line that can turn a finding into something that journals, readers, and careers treat as meaningful.

The source’s warning is that a threshold can become an incentive target. When researchers have many plausible analytical choices, P-Hacking can move a result onto the publishable side of the cutoff without making the underlying claim more robust.

Key Claims

• A significance threshold is a convention for interpreting uncertainty, not a guarantee that a claim is true.
• The episode treats the 5 percent line as especially powerful because journals often prefer significant results.
• Bunching near the threshold can reveal Publication Bias, analysis tuning, or selective submission.
• Robustness Checks matter because a result that only survives one narrow specification may be statistically significant but substantively fragile.
• Preregistration can help keep the threshold from becoming a moving target after researchers see the data.

Connections

• P-Hacking - failure mode when researchers search across many choices for significance.
• Publication Bias - institutional pressure attached to crossing the cutoff.
• Replication Crisis - broader credibility problem.
• Scientific Skepticism and Rational Humility - interpretation posture for statistical evidence.