A false positive occurs when analysis suggests an effect or improvement that does not actually exist.
False positives often result from noise or insufficient data.
Examples in Action
- Early test results appearing significant
- Small sample sizes
- High metric volatility
- Overinterpretation of short-term change
Typical Outcomes / Results
- Reduced confidence when uncorrected
- Wasted implementation effort
- Improved discipline when identified
- Stronger experimentation practices
This definition reflects standard statistical interpretation.