Whenever there is an increased probability of accepting null when null should have been rejected, then
A) the Type 2 error is increased
B) the power is decreased
C) there is a decreased likelihood of obtaining significance
D) all of these

Question

Quizplus · Accepted Answer

When there is an increased probability of accepting null when null should have been rejected, it means the test has a higher chance of committing a Type 2 error, which is failing to reject a false null hypothesis. This in turn decreases the power of the test to detect a true alternative hypothesis, and there is a decreased likelihood of obtaining significance as the test becomes less sensitive to detecting a significant difference. Therefore, all of the choices (A, B, and C) are correct.

Whenever There Is an Increased Probability of Accepting Null When