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Approximately 2.5 percent of all people have red hair. Of the people who have red hair, 22 percent are brown eyed. Of the people who don't have red hair, 35 percent aren't brown eyed.

(a) Make a tree diagram to model the situation.



(b) What is the probability that a randomly selected person is brown eyed?



(c) What is the probability that a randomly selected person
has red hair given the person selected isn't brown eyed?



(d) A random sample of 20 people will be selected. What is the probability that the sample will have
at least 1 person with red hair?

1 Answer

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Answer:

Explanation:

(a) Here is a tree diagram to model the situation:

P(red hair)=0.025

/ \

P(brown eyed | red hair)=0.22 P(not brown eyed | red hair)=0.78

/ \

P(brown eyed | not red hair)=0.65 P(not brown eyed | not red hair)=0.35

(b) The probability that a randomly selected person is brown eyed is equal to the sum of the probabilities of being brown eyed given red hair and being brown eyed given not red hair, weighted by the probabilities of having red hair and not having red hair:

P(brown eyed) = P(brown eyed | red hair) * P(red hair) + P(brown eyed | not red hair) * P(not red hair)

= 0.22 * 0.025 + 0.65 * (1 - 0.025)

= 0.6385

Therefore, the probability that a randomly selected person is brown eyed is approximately 0.6385, or 63.85%.

(c) The probability that a randomly selected person has red hair given the person selected isn't brown eyed can be calculated using Bayes' theorem:

P(red hair | not brown eyed) = P(not brown eyed | red hair) * P(red hair) / P(not brown eyed)

To calculate the denominator, we need to use the law of total probability, which states that the probability of an event is equal to the sum of the probabilities of that event given each possible condition:

P(not brown eyed) = P(not brown eyed | red hair) * P(red hair) + P(not brown eyed | not red hair) * P(not red hair)

= 0.78 * 0.025 + 0.35 * (1 - 0.025)

= 0.3685

Substituting this and the other given probabilities into Bayes' theorem, we get:

P(red hair | not brown eyed) = 0.78 * 0.025 / 0.3685

≈ 0.0529

Therefore, the probability that a randomly selected person has red hair given the person selected isn't brown eyed is approximately 0.0529, or 5.29%.

(d) The probability that a sample of 20 people will have at least 1 person with red hair can be calculated using the complement rule, which states that the probability of an event happening is equal to 1 minus the probability of the event not happening. In this case, the event of interest is that none of the 20 people have red hair, so the probability of this event happening is:

P(none have red hair) = (1 - 0.025)^20

≈ 0.3585

Therefore, the probability that at least 1 person in the sample has red hair is:

P(at least 1 has red hair) = 1 - P(none have red hair)

≈ 0.6415

So, the probability that a sample of 20 people will have at least 1 person with red hair is approximately 0.6415, or 64.15%.

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