400 Suppose a particular surveillance system has a 99% chance of correctly identifying a future terrorist and a 99.8% chance of correctly identifying someone who is not a future terrorist. If there are 1,000 future terrorists in a population of 400 million, and one of these 400 million is randomly selected, scrutinized by the system, and identified as a future terrorist, what is the probability that he/she actually is a future terrorist

1.236 × 10^(-3)

Step-by-step explanation:

Let A be the event that the person is a future terrorist

Let B the event that the person is identified as a terrorist

We are told that there are 1,000 future terrorists in a population of 400 million. Thus, the Probability that the person is a terrorist is;

P(A) = 1000/400000000

P(A) = 0.0000025

P(A') = 1 - P(A)

P(A') = 1 - 0.0000025

P(A') = 0.9999975

We are told that the system has a 99% chance of correctly identifying a future terrorist. Thus; P(B|A) = 0.99

Thus, P(B'|A) = 1 - P(B|A)

P(B'|A) = 1 - 0.99

P(B'|A) = 0.01

We are told that there is a 99.8% chance of correctly identifying someone who is not a future terrorist. Thus; P(B'|A') = 0.998

Hence: P(B|A') = 1 - P(B'|A')

P(B|A') = 1 - 0.998

P(B|A') = 0.002

We want to find the probability that someone who is identified as a terrorist, is actually a future terrorist. This is represented by: P(A|B)

We can find it from bayes theorem as follows;

P(A|B) = [P(B|A) × P(A)]/[(P(B|A) × P(A)) + (P(B|A') × P(A')]

Plugging in the relevant values;

P(A|B) = [0.99 × 0.0000025]/[(0.99 × 0.0000025) + (0.002 × 0.9999975)]

P(A|B) = 0.00123597357 = 1.236 × 10^(-3)

the workers who do no drive has no reasonable reason to buy gasoline due to they don't have anything to use it for

answer:   y=2x-3

step-by-step explanation: