Evidence-appraisal glossary
Type I error
A type I error is rejecting a null hypothesis that is actually true, that is, concluding there is an effect when there is none. It is a false positive.
Also called: false positive, alpha error.
The alpha level sets the long-run rate of type I errors a study is willing to accept, commonly 5 percent, so testing many outcomes at that threshold makes at least one false positive increasingly likely. The rate applies to a decision rule across many hypothetical studies; it is not the probability that any single significant finding is a fluke.
This is a plain-language methodology definition for reading research. It is general education, not medical advice.