Probability and Statistical Biases

P-hacking

Trying analyses until a significant result appears.

What Is P-hacking?

P-hacking is a thinking trap where trying analyses until a significant result appears.

How It Tricks You

It can make noisy, incomplete, or poorly framed data feel more meaningful than it is.

Real-World Example

A researcher keeps adjusting analysis until a significant result appears.

Seen Online As

• We found a stat that works if we slice the data this way.
• One significant result is being treated like the whole story.
• The analysis kept changing until something looked meaningful.

What To Ask Instead

Was the analysis plan set in advance?

Related Thinking Traps

• Anchoring bias
• Confirmation bias
• Framing effect
• Loss aversion

Common Situations

• Thinking Traps at Work

Quick FAQ

What is P-hacking?

Trying analyses until a significant result appears.

What is an example of P-hacking?

A researcher keeps adjusting analysis until a significant result appears.

How do I spot P-hacking?

Was the analysis plan set in advance?