Consider an increase in the size of the test used to examine a hypothesis from 5% to 10%. Which one of the following would be an implication?
A) The probability of a Type I error is increased
B) The probability of a Type II error is increased
C) The rejection criterion has become more strict
D) The null hypothesis will be rejected less often.

Question

Quizplus · Accepted Answer

Increasing the size of the test (also known as the significance level) from 5% to 10% means that the researcher is willing to accept a higher probability of rejecting the null hypothesis when it is actually true, which is the definition of a Type I error. Therefore, the probability of committing a Type I error increases.

Consider an Increase in the Size of the Test Used