Hypothesis Testing with One Sample
Read this section on the two types of errors in hypothesis testing and some examples of each.
Type I Error
A type I error occurs when the null hypothesisis true but is rejected. It is asserting something that is absent, a false hit. A type I error may be compared with a so-called false positive (a result that indicates that a given condition is present when it actually is not present) in tests where a single condition is tested for. A type I error can also be said to occur when we believe a falsehood. In terms of folk tales, an investigator may be "crying wolf" without a wolf in sight (raising a false alarm). : no wolf.
The rate of the type I error is called the size of the test and denoted by the Greek letter(alpha). It usually equals the significance level of a test. In the case of a simple null hypothesis, is the probability of a type I error. If the null hypothesis is composite, is the maximum of the possible probabilities of a type I error.