During the testing of hypotheses, we can commit type I and type II errors. Type I errors refer to the rejection of the true null hypothesis (called a false positive), and type II errors (false negative) refer to a failure to reject a false null hypothesis. An example of the first case is a patient being diagnosed for a disease he does not have, while an example of the second case is a diagnosis failing to identify an existing disease.