(10 points) A test for a certain drug produces a false negative 3% of the time and a false positive 9% of the time. Suppose 12% of the employees at a certain company use the drug. If an employee at the company tests negative, what is the probability that he or she does use the drug

If an employee at the company tests negative, the probability that he or she does use the drug is P=0.58.

Step-by-step explanation:

We have this information:

proportion of drug users P(D)=0.12

false negatives FN=P(N|D)=0.03 --> True negatives P(N|ND)=0.97

false positives FP=P(P|ND)=0.09 --> True positives P(P|D)=0.91

where:

D: drug user

ND: no drug user

N: negative result

P: positive result

We have to calculate the probability that, given a positive teste, the person is a drug user.

Applying the Bayes theorem, we have:

it depends on the weather. because i have flown to seattle when it was pouring down rain and there was one time i flew to ohio when it was snowing hard. whats your situation.

step-by-step explanation:

56.6

step-by-step explanation:

the ratio of the perimeters is equal to the scale.

the ratio of the areas is equal to the square of the scale.

34 / 20 = k

a / 19.6 = k²

substituting:

a / 19.6 = (34 / 20)²

a = 19.6 (34 / 20)²

a ≈ 56.6