Detecting a false difference, or declaring that the x influences Y when it’s only random variation. Also known as “alpha (α) risk.”
A type I error, also known as an error of the first kind, is the wrong decision that is made when a test rejects a true null hypothesis (H0). A type I error may be compared with a so called false positive in other test situations. Type I error can be viewed as the error of excessive credulity. In terms of folk tales, an investigator may be "crying wolf" (raising a false alarm) without a wolf in sight (H0: no wolf). The rate of the type I error is called the size of the test and denoted by the Greek letter α (alpha). It usually equals the significance level of a test. In the case of a simple null hypothesis α is the probability of a type I error. If the null hypothesis is composite, α is the maximum (supremum) of the possible probabilities of a type I error.