Answer :
Answer:
Step-by-step explanation:
a) The probability of a Type I error in a lie detection test would be the probability that the lie detection machine incorrectly detected lie for the truth tellers. This is already given in the problem as 0.07.
Therefore,
[tex]P(Type-I) = 0.07[/tex]
Therefore 0.07 is the required probability here.
b) The probability of a Type II error in a lie detection test would be the probability that the lie detection machine incorrectly detected truth for the the people who are actually liars. This is thus 1 - reliability.
[tex]P(Type-II) = 1 - Reliability = 1- 0.86 = 0.14[/tex]
Therefore 0.14 is the required probability here.
Answer:
a) 0.070
b) 0.14
Step-by-step explanation:
Given that the tests are 86% reliable, i.e a probability of 0.86 a lie would be detected.
Probability of error = 0.070
a) For type I error, we have:
The probability of a type I error in this lie detector is the probability that the test erroneously detects a lie even when the individual is actually telling the truth, i.e
P(type I error) = P(rejecting true null)
= 0.070
b) The probability of a Type II error this lie detectot is the probability that the test erroneously detected truth insteax of lie.
i.e = 1 - reliability
P (Type II error) = P(Failing to reject false Null)
= P(Not detecting a lie)
= 1-0.86
= 0.14