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In Exercises 5鈥8, use the relatively small number of given bootstrap samples to construct the confidence interval.Seating Choice In a 3M Privacy Filters poll, respondents were asked to identify their favourite seat when they fly, and the results include these responses: window, window, other, other. Letting 鈥渨indow鈥 = 1 and letting 鈥渙ther鈥 = 0, here are ten bootstrap samples for those responses: {0, 0, 0, 0}, {0, 1, 0, 0}, {0, 1, 0, 1}, {0, 0, 1, 0}, {1, 1, 1, 0}, {0, 1, 1, 0}, {1, 0, 0, 1}, {0, 1, 1, 1}, {1, 0, 1, 0}, {1, 0, 0, 1}. Using only the ten given bootstrap samples, construct an 80% confidence interval estimate of the proportion of respondents who indicated their favourite seat is 鈥渨indow.鈥

Short Answer

Expert verified

The 80% confidence interval estimate of the population proportion of respondents who prefer the window seat is equal to (0.125,0.75).

Step by step solution

01

Given information

10 bootstrap samples of responses on the favourite seat of the respondents when they fly are considered. 鈥淲indow鈥 is denoted by 1, and 鈥淥ther鈥 is denoted by 0.

The ten samples are:

{0, 0, 0, 0}, {0, 1, 0, 0}, {0, 1, 0, 1}, {0, 0, 1, 0}, {1, 1, 1, 0}, {0, 1, 1, 0}, {1, 0, 0, 1}, {0, 1, 1, 1}, {1, 0, 1, 0} and {1, 0, 0, 1}.

02

Expression of the confidence intervals

The 80% confidence interval estimate of the population proportion has the following expression:

P10<p<P90

Here, P10denotes the 10th percentile of the sorted sample proportions and P90denotes the 90th percentile of the sorted sample proportions.

03

Find the sample proportion from each bootstrap sample

The following formula of the sample proportion is used to compute the sample proportions of each of the 10 bootstrap samples:

p^=xn

Here, denotes the number of respondents who prefer window seats, and n is the sample size.

The value of n is the same for all samples and is equal to 4.

The sample proportion for the first bootstrap sample is computed below

The number of 1s in the first sample is the value of x1.

p^1=x1n1=04=0

Similarly, the sample proportions of the remaining 9 bootstrap samples are computed.

The following table shows the sample proportions of each of the 10 bootstrap samples:

Sample number

Bootstrap samples

Sample proportion

1

0

0

0

0

0

2

0

1

0

0

0.25

3

0

1

0

1

0.5

4

0

0

1

0

0.25

5

1

1

1

0

0.75

6

0

1

1

0

0.5

7

1

0

0

1

0.5

8

0

1

1

1

0.75

9

1

0

1

0

0.5

10

1

0

0

1

0.5

The following table shows the sorted values of the sample proportions in ascending order:

0

0.25

0.25

0.5

0.5

0.5

0.5

0.5

0.75

0.75

04

Find the percentiles

For finding the percentile, first, compute the value of the locator (L) as follows.

L=k100n

Here, k is the percentile value, and n is the total number of observations.

a.

For finding the 10th percentile of the sorted values, first, find the value of L.

Here, n is equal to 10, and k is equal to 5.

Thus,

L=k100n=1010010=1

As L is a whole number, the value of P10is the sum of the Lthand theL+1th sample proportions divided by 2.

P10=1stsampleproportion+2ndsampleproportion2=0+0.252=0.125

Thus, P10is equal to 0.125.

For finding the 90th percentile, first, find the value of L.

L=k100n=9010010=9

As L is a whole number, the value of P90is the sum of the Lthand L+1ththe sample proportions divided by 2.

P90=9thsampleproportion+10thsampleproportion2=0.75+0.752=0.75

Thus, P90is equal to 0.75.

05

Confidence interval estimate of the population proportion

The 80% confidence interval estimate of the population proportion of respondents who prefer the window seat using the bootstrap samples is as follows.

P10<p<P90=0.125<p<0.75

Thus, the 80%confidence intervalestimate of the population proportion of respondents who prefer the window seat is equal to (0.125,0.75).

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Most popular questions from this chapter

Normality Requirement What does it mean when we say that the confidence interval methodsof this section are robust against departures from normality?

Cell Phone Radiation Here is a sample of measured radiation emissions (cW/kg) for cell phones (based on data from the Environmental Working Group): 38, 55, 86, 145. Here are ten bootstrap samples: {38, 145, 55, 86}, {86, 38, 145, 145}, {145, 86, 55, 55}, {55, 55, 55, 145}, {86, 86, 55, 55}, {38, 38, 86, 86}, {145, 38, 86, 55}, {55, 86, 86, 86}, {145, 86, 55, 86}, {38, 145, 86, 556}.

a. Using only the ten given bootstrap samples, construct an 80% confidence interval estimate of the population mean.

b. Using only the ten given bootstrap samples, construct an 80% confidence interval estimate of the population standard deviation.

Sample Size. In Exercises 29鈥36, find the sample size required to estimate the population mean.

Mean Pulse Rate of Males Data Set 1 鈥淏ody Data鈥 in Appendix B includes pulse rates of 153 randomly selected adult males, and those pulse rates vary from a low of 40 bpm to a high of 104 bpm. Find the minimum sample size required to estimate the mean pulse rate of adult males. Assume that we want 99% confidence that the sample mean is within 2 bpm of the population mean.

a. Find the sample size using the range rule of thumb to estimate .

b. Assume that =11.3bpm, based on the value of s=12.5bpmfor the sample of 153 male pulse rates.

c. Compare the results from parts (a) and (b). Which result is likely to be better?

Critical Thinking. In Exercises 17鈥28, use the data and confidence level to construct a confidence interval estimate of p, then address the given question. Smoking Stopped In a program designed to help patients stop smoking, 198 patients were given sustained care, and 82.8% of them were no longer smoking after one month. Among 199 patients given standard care, 62.8% were no longer smoking after one month (based on data from 鈥淪ustained Care Intervention and Post discharge Smoking Cessation Among Hospitalized Adults,鈥 by Rigottiet al., Journal of the American Medical Association, Vol. 312, No. 7). Construct the two 95% confidence interval estimates of the percentages of success. Compare the results. What do you conclude?

In Exercises 9鈥16, assume that each sample is a simple

random sample obtained from a population with a normal distribution.

Comparing Waiting Lines

a. The values listed below are waiting times (in minutes) of customers at the Jefferson Valley Bank, where customers enter a single waiting line that feeds three teller windows. Construct a95% confidence interval for the population standard deviation .

6.5 6.6 6.7 6.8 7.1 7.3 7.4 7.7 7.7 7.7

b. The values listed below are waiting times (in minutes) of customers at the Bank of Providence, where customers may enter any one of three different lines that have formed at three teller windows. Construct a 95% confidence interval for the population standard deviation .

4.2 5.4 5.8 6.2 6.7 7.7 7.7 8.5 9.3 10.0

c. Interpret the results found in parts (a) and (b). Do the confidence intervals suggest a difference in the variation among waiting times? Which arrangement seems better: the single-line system or the multiple-line system?

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