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kakasveta [241]
3 years ago
5

all a household prosperous if its income exceeds $100,000. Call the household educated if the householder completed college. Sel

ect an American household at random, and let A be the event that the selected household is prosperous and B the event that it is educated. According to a survey, P(A) = 0.137, P(B) = 0.272, and the probability that a household is both prosperous and educated is P(A and B) = 0.082. What is the conditional probability that a household is prosperous, given that it is educated? (Round your answer to four decimal places.)
Mathematics
1 answer:
7nadin3 [17]3 years ago
6 0

Answer:

A= the event that the selected household is prosperous

B= the event that the selected household is educated

P(A) =0.137, P(B) =0.272, P(A \cap B) =0.082

P(A|B)= \frac{0.082}{0.272}= 0.3015

And that represent the final answer for this case.

Step-by-step explanation:

For this case we define the following events:

A= the event that the selected household is prosperous

B= the event that the selected household is educated

We have the following probabilities given:

P(A) =0.137, P(B) =0.272, P(A \cap B) =0.082

For this case we want to calculate the conditional probability that a household is prosperous, given that it is educated.

So this probability can be expressed as P(A|B)

Using the Bayes rule we know that:

P(A|B) = \frac{P(A \cap B)}{P(B)}

And for this case we have everything in order to replace, and we got:

P(A|B)= \frac{0.082}{0.272}= 0.3015

And that represent the final answer for this case.

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Complete Question

Find the​ mean, variance, and standard deviation of the binomial distribution with the given values of n and p. ​, The​ mean, ​, is nothing. ​(Round to the nearest tenth as​ needed.)

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The standard deviation \sigma =  2.08

The  variance   var  = 4.32

Step-by-step explanation:

From the question we are told that

      The probability of success   is  p = 0.6

      The  sample size is n = 18

  Generally given that the distribution is binomial, then the probability of failure is mathematically represented as

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              q =0.4

Generally the mean is mathematically evaluated as

             \mu  =  np

substituting values

             \mu  =  18 * 0.6    

             \mu  = 10.5

The  standard deviation is evaluated as

              \sigma =  \sqrt{npq}

substituting values

               \sigma =  \sqrt{18 *  0.6 * 0.4}

              \sigma =  2.08

The variance is evaluated as

               var  =  \sigma^2

substituting value

              var  = 2.08^2

              var  = 4.32

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