What is it?

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.