Statistical hypothesis tests are used to make a decision about whether the null hypothesis should be accepted or rejected. Since these conclusions are based on sample data, there is a risk of incorrect decision. There are two types of incorrect decisions through hypothesis testing: type I error and type II error. Type I error is defined as rejecting the null hypothesis (H0 ) when it is actually true. On the other hand, Type II error is defined as failing to reject the null hypothesis (H0 ) when it is actually false.