Answer:
A) P(Type I error) = 0.045
B) P(Type II) error = 0.1
Step-by-step explanation:
We are told that the reliability of the test is 90% reliable.
Also, we are told that the probability that the test erroneously detects a lie even when the individual is actually telling the truth is 0.045.
Thus;
A) To calculate the probability of type I error:
From statistics, in this question we can say that the probability of a type I error is the probability that the test will erroneously detect a lie even though the individual is actually telling the truth. Thus;
Probability of (type I error) = P(rejecting true null) = 0.045
B) For probability of type II error, it is defined as the error where we accept a null hypothesis that is false. We can say that it produces a false negative and the formula is;
P(Type II) error = 1 - reliability
Reliability in the question is 0.90
Thus;
P(Type II) error = 1 - 0.9
P(Type II) error = 0.1
