Type I Error
01 Definition
Type I Error meaning: A false positive: concluding a change works when it actually does not.
A Type I error happens when a test reports a real difference that is not there, rejecting the null hypothesis by mistake. The confidence level sets how often this can happen; a 95 percent level allows about a 5 percent chance. Running many tests or peeking early raises the risk.
Also called
Why it matters
How Type I Error fits the work
Understanding Type I error keeps teams from rolling out changes that only appeared to win, which wastes effort and can quietly hurt performance.
In context
The tool flagged the new banner as a winner, but a repeat test showed no lift, revealing the first result as a Type I error.
Practical note
Every test carries some false positive risk, and testing many variants multiplies it. Confirm surprising wins with a follow-up test before committing major resources.