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In February 2008, the Gallup organization surveyed 1,034 adults between 30 and 64 years of age and found that 548 were worried that they will outlive their money after they retire. Does the sample evidence suggest that a majority of 30- to 64-year-olds in the United States are worried they will outlive their money? Use the a 0.05 level 2. of significance: (a) Regarding a population proportion, what condition must be provided? (b) Determine the alternative hypothesis if the null hypothesis is p (c) Show the critical value approach. (d) Show the P-value approach. 0.5. (e) Decide whether you reject the null hypothesis or not. Then state the conclusion.
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Answer #1

Solution:

Given:

n = sample size = Number of adults surveyed between 30 and 64 years of age = 1034

x = Number of adults worried that they will outlive their money after they retire = 548

We have to test if their is sample evidence to suggest that a majority of 30-to 64-years-old's in the United Status are worried they will outlive their money.

Level of significance = \alpha = 0.05

Part a)

Regarding population proportion, following condition must me provided:

n \times p \geq 10

and n \times (1-p) \geq 10

where p = population proportion = 0.5

n \times p = 1034 \times 0.5 = 517 > 10

and

n \times (1-p) = 1034 \times (1-0.5) = 1034 \times 0.5 = 517 > 10

Thus both the conditions are satisfied.

Thus sampling distribution of sample proportions is approximately Normal with mean of sample proportions is:

\mu_{\hat{p}} = p

\mu_{\hat{p}} = 0.5

and standard deviation of sample proportions is:

\sigma_{\hat{p}}= \sqrt{\frac{p \times (1-p)}{n}}

\sigma_{\hat{p}}= \sqrt{\frac{0.5 \times (1-0.5)}{1034}}

\sigma_{\hat{p}}= \sqrt{\frac{0.5 \times 0.5 }{1034}}

\sigma_{\hat{p}}= \sqrt{ 0.000241779 }

\sigma_{\hat{p}}= 0.015549

Part b)

Null hypothesis is : p = 0.5

Thus alternative hypothesis is: p > 0.5, since we have to test majority of 30-to 64-years-old's in the United Status are worried they will outlive their money, that is: we have to test population proportion is more than 0.5.

Thus

H0: p= 0.5 Vs H1: p > 0.5

Part c) Critical value approach:

We need to find z test statistic value and z critical value.

z test statistic value:

z= \frac{\hat{p}-\mu_{\hat{p}}}{ \sigma_{\hat{p}} }

where

\hat{p} = \frac{x}{n} = \frac{548}{1034}=0.53

thus

z= \frac{\hat{p}-\mu_{\hat{p}}}{ \sigma_{\hat{p}} }

z= \frac{0.53 - 0.5}{ 0.015549 }

z= \frac{0.03}{ 0.015549 }

z= 1.93

and

z critical value:

Since this is right tailed test, find area = 1 - 0.05 = 0.95

Look in z table for Area = 0.9500 or its closest area and find corresponding z value.

Area 0.9500 is in between 0.9495 and 0.9505 and both the area are at same distance from 0.9500

Thus we look for both area and find both z values

Thus Area 0.9495 corresponds to 1.64 and 0.9505 corresponds to 1.65

Thus average of both z values is : ( 1.64+1.65) / 2 = 1.645

Thus Zcritical = 1.645

Part d) Show the P-value approach:

P-value = P( Z > z test statistic )

P-value = P( Z > 1.93 )

P-value = 1 - P( Z < 1.93 )

Look in z table for z = 1.9 and 0.03 and find corresponding area.

P( Z < 1.93 ) = 0.9732

Thus

P-value = 1 - P( Z < 1.93 )

P-value = 1 - 0.9732

P-value = 0.0268

Part e) Decision and Conclusion:

Decision using Critical value:

Since this is right tailed test, rejection region would be:

Reject null hypothesis ,if z test statistic value > z critical value = 1.645 , otherwise we fail to reject H0.

Since z test statistic value = 1.93 > z critical value = 1.645 , we reject null hypothesis.

Decision using P-value:

Reject H0, if P-value < 0.05 level of significance, otherwise we fail to reject H0.

Since P-value = 0.0268 < 0.05 level of significance, we reject null hypothesis.

Conclusion:

Since we have rejected null hypothesis, we have enough evidence to suggest that a majority of 30-to 64-years-old's in the United Status are worried they will outlive their money.

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