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Based on historical data, your manager believes that 26% of the company's orders come from first-time customers. A random sample of 158 orders will be used to estimate the proportion of first-time-customers. What is the probability that the sample proportion is greater than than 0.4?

Note: You should carefully round any z-values you calculate to 4 decimal places to match wamap's approach and calculations.



Answer =


(Enter your answer as a number accurate to 4 decimal places.)

1 Answer

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Answer:


\hat p \sim N( p, \sqrt{(p (1-p))/(n)})

And we can use the z score formula given by:


z = (\hat p -\mu_p)/(\sigma_p)

And if we find the parameters we got:


\mu_p = 0.26


\sigma_p = \sqrt{(0.26(1-0.26))/(158)} = 0.0349

And we can find the z score for the value of 0.4 and we got:


z = (0.4-0.26)/(0.0349)= 4.0119

And we can find this probability:


P(z>4.0119) = 1-P(z<4.0119)

And if we use the normal standard table or excel we got:


P(z>4.0119) = 1-P(z<4.0119)=1-0.99997 = 0.00003

Explanation:

For this case we have the following info given:


p = 0.26 represent the proportion of the company's orders come from first-time customers


n=158 represent the sample size

And we want to find the following probability:


p(\hat p >0.4)

And we can use the normal approximation since we have the following two conditions:

1) np = 158*0.26 = 41.08>10

2) n(1-p) = 158*(1-0.26) = 116.92>10

And for this case the distribution for the sample proportion is given by:


\hat p \sim N( p, \sqrt{(p (1-p))/(n)})

And we can use the z score formula given by:


z = (\hat p -\mu_p)/(\sigma_p)

And if we find the parameters we got:


\mu_p = 0.26


\sigma_p = \sqrt{(0.26(1-0.26))/(158)} = 0.0349

And we can find the z score for the value of 0.4 and we got:


z = (0.4-0.26)/(0.0349)= 4.0119

And we can find this probability:


P(z>4.0119) = 1-P(z<4.0119)

And if we use the normal standard table or excel we got:


P(z>4.0119) = 1-P(z<4.0119)=1-0.99997 = 0.00003

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