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At LaGuardia Airport for a certain nightly flight, the probability that it will rain is 0.08 and the probability that the flight will be delayed is 0.12 . The probability that it will not rain and the flight will leave on time is 0.84 . What is the probability that it is raining and the flight is delayed? Round your answer to the nearest thousandth.
Answer:

At LaGuardia Airport for a certain nightly flight, the probability that it will rain is 00.0808 and the probability that the flight will be delayed is 00.1212 . The probability that it will not rain and the flight will leave on time is 00.8484 . What is the probability that it is raining and the flight is delayed? Round your answer to the nearest thousandth.\newlineAnswer:

Full solution

Q. At LaGuardia Airport for a certain nightly flight, the probability that it will rain is 00.0808 and the probability that the flight will be delayed is 00.1212 . The probability that it will not rain and the flight will leave on time is 00.8484 . What is the probability that it is raining and the flight is delayed? Round your answer to the nearest thousandth.\newlineAnswer:
  1. Events Denotation: Let's denote the events as follows:\newlineR: It will rain.\newlineD: The flight will be delayed.\newlineN: It will not rain and the flight will leave on time.\newlineWe are given the following probabilities:\newlineP(R)=0.08P(R) = 0.08\newlineP(D)=0.12P(D) = 0.12\newlineP(N)=0.84P(N) = 0.84\newlineWe need to find the probability that it is raining and the flight is delayed, which is P(R and D)P(R \text{ and } D).
  2. Find P(R or D)P(R \text{ or } D): First, we need to find the probability that it will rain or the flight will be delayed, which is P(R or D)P(R \text{ or } D). This can be found using the complement of the probability that it will not rain and the flight will leave on time, which is P(N)P(N).\newlineSince P(N)P(N) is the probability that it will not rain and the flight will leave on time, the complement is the probability that it will rain or the flight will be delayed, so:\newlineP(R or D)=1P(N)P(R \text{ or } D) = 1 - P(N)\newlineP(R or D)=10.84P(R \text{ or } D) = 1 - 0.84\newlineP(R or D)=0.16P(R \text{ or } D) = 0.16
  3. Use Inclusion-Exclusion Principle: Now, we can use the Inclusion-Exclusion Principle to find P(R and D)P(R \text{ and } D). The principle states:\newlineP(R or D)=P(R)+P(D)P(R and D)P(R \text{ or } D) = P(R) + P(D) - P(R \text{ and } D)\newlineWe can rearrange this formula to solve for P(R and D)P(R \text{ and } D):\newlineP(R and D)=P(R)+P(D)P(R or D)P(R \text{ and } D) = P(R) + P(D) - P(R \text{ or } D)\newlineSubstituting the values we have:\newlineP(R and D)=0.08+0.120.16P(R \text{ and } D) = 0.08 + 0.12 - 0.16\newlineP(R and D)=0.200.16P(R \text{ and } D) = 0.20 - 0.16\newlineP(R and D)=0.04P(R \text{ and } D) = 0.04

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