Type I error, also known as a “false positive”: the error of rejecting a null
hypothesis when it is actually true. In other words, this is the error of accepting an
alternative hypothesis (the real hypothesis of interest) when the results can be
attributed to chance. Plainly speaking, it occurs when we are observing a
difference when in truth there is none (or more specifically - no statistically
significant difference). So the probability of making a type I error in a test with
rejection region R is 0 P R H ( | is true) .