Answer:
Correct option: Type II error.
Step-by-step explanation:
In statistical hypothesis testing two kind of errors can be committed by the researcher.
- Type I error: The probability of rejecting a null hypothesis when in fact it is true.
- Type II error: The probability of not rejecting a null hypothesis when in fact it is false.
The power of the test is defined as the probability of rejecting a false null hypothesis. It is denoted by <em>β</em>.
Then the probability of Type II error can be defined as:
P (Type II error) = 1 - <em>β</em>.
The power of the test is affected by the significance level<em>.</em>
If the significance level is less than the power is also less.
The significance level is related to the <em>p</em>-value of the test.
So the P(Correct) = 1 - <em>p</em>-value.