How Do You Set The Significance Level When Testing One Population Parameter?
The significance level determines the maximum probability of making a type I error. In order to test the null hypothesis, one must set the significance level before working the problem. A type I error occurs when the null hypothesis is true but is rejected. On the other hand, a type II error occurs when the null hypothesis is false but is not rejected. Determine which type of Error (Type I or Type II) is costly. Reminder a Type I error occurs when the null hypothesis is rejected when it is actually true and a type II error occurs when the null hypothesis is accepted but it is actually false. If type I error is more costly than a type II error, set the significance level low, such as .01. If a type II error is more costly, set the significance level high, such as .1. If both types of errors are costly, set the signifiance level at a medium level, such as .05.
