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kifflom [539]
3 years ago
14

A courier service company wishes to estimate the proportion of people in various states that will use its services. Suppose the

true proportion is 0.04. If 469 are sampled, what is the probability that the sample proportion will be less than 0.03
Mathematics
1 answer:
a_sh-v [17]3 years ago
5 0

Answer:

Probability that the sample proportion will be less than 0.03 is 0.10204.

Step-by-step explanation:

We are given that a courier service company wishes to estimate the proportion of people in various states that will use its services. Suppose the true proportion is 0.04.

Also, 469 are sampled.

<em>Let </em>\hat p<em> = sample proportion</em>

The z-score probability distribution for sample proportion is given by;

              Z = \frac{ \hat p-p}{\sqrt{\frac{\hat p(1-\hat p)}{n} } }  ~ N(0,1)

where, \hat p = sample proportion

           p = true proportion = 0.04

           n = sample size = 469

The Z-score measures how many standard deviations the measure is away from the mean. After finding the Z-score, we look at the z-score table and find the p-value (area) associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X.

So, probability that the sample proportion will be less than 0.03 is given by = P( \hat p < 0.03)

       P( \hat p < 0.03) = P( \frac{ \hat p-p}{\sqrt{\frac{\hat p(1-\hat p)}{n} } } < \frac{0.03-0.04}{\sqrt{\frac{0.03(1-0.03)}{469} } } ) = P(Z < -1.27) = 1 - P(Z \leq 1.27)

                                                                      = 1 - 0.89796 = 0.10204

Now, in the z table the P(Z \leq x) or P(Z < x) is given. So, the above probability is calculated by looking at the value of x = 1.27 in the z table which has an area of 0.89796.

Therefore, probability that the sample proportion will be less than 0.03 is 0.10204.

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Step-by-step explanation:

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and

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Answer:

a) Z = 1.2

b) 38.49% of the population is between 19 and 25.

c) 34.46% of the population is less than 17.

Step-by-step explanation:

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In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by

Z = \frac{X - \mu}{\sigma}

After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X. If we need to find the probability that the measure is larger than X, it is 1 subtracted by this pvalue.

For this problem, we have that

A normal population has a mean of 19 and a standard deviation of 5, so \mu = 19, \sigma = 5.

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This is Z when X = 25

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(b) What proportion of the population is between 19 and 25?

This is the pvalue of Z when X = 25 subtracted by the pvalue of Z when X = 19.

X = 25 has Z = 1.2, that has a pvalue of 0.8849.

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So 0.8849-0.500 = 0.3849 = 38.49% of the population is between 19 and 25.

(c) What proportion of the population is less than 17?

This is the pvalue of Z when X = 17

Z = \frac{X - \mu}{\sigma}

Z = \frac{17 - 19}{5}

Z = -0.40

Z = -0.40 has a pvalue of 0.3446.

This means that 34.46% of the population is less than 17.

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Step-by-step explanation:

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