A Type I error occurs in hypothesis testing when the null hypothesis is incorrectly rejected when it is actually true. This means that the test indicates there is a significant effect or difference when, in reality, there is none, leading to a false positive conclusion.

A Type I error occurs when you reject the null hypothesis (H0) when it is actually true.

A Type I error in hypothesis testing happens when the null hypothesis is wrongly rejected while it is true. This implies that the test suggests a significant effect or difference exists when, in fact, there is none, resulting in a false positive outcome.