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
Answer:
30 4/5 or 30.8
Step-by-step explanation:
8 divided by 2 and 18 divided by 2 so 4/9
Answer:
$960
Step-by-step explanation:
Let the original amount be = x
Percentage increase is equal to = 12.5%
final amount = original amount + increase
final amount = x + 0.125x
final amount = 1.125x
final amount = 1080 = 1.125x
and then solve for x
so in the end x is equal to $960
Solve the equation: 1080 = 1.25x
Then the probability of any of the others being selected after that is 1/9 because there is one less to choose from.
