Consider a test for using a particular drug. The test will produce 99% true positive results for drug users and 99% true negative results for non-drug users. Suppose that 0.5% of people are users of the drug. What is the probability that a randomly selected individual with a positive test is a drug user?

Step-by-step explanation:

Using  Bayes' theorem, we have:

is a conditional probability: the likelihood of event A occurring, given that B is true.

is also a conditional probability: the likelihood of event B occurring, given that A is true.

P(A) and P(B) are the marginal probabilities of observing A and B, independently of each other.

We solve thus:

                 =

                 =

                 =

                 =

                 = or %

Therefore, if an individual tests positive, it is more likely than not (1 - 33.2% = 66.8%) that they do not use the drug.

the answer is 150.6

step-by-step explanation:

you multiply .02 by 30 and get .6.

and then you multiply 5.00 by 30 and get 150.

hope this !

step-by-step explanation:

your answer is a