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Exercises 3.112 to 3.115 give information about the proportion of a sample that agree with a certain statement. Use StatKey or other technology to find a confidence interval at the given confidence level for the proportion of the population to agree, using percentiles from a bootstrap distribution. StatKey tip: Use "CI for Single Proportion" and then "Edit Data" to enter the sample information. Find a \(90 \%\) confidence interval if 112 agree and 288 disagree in a random sample of 400 people.

Short Answer

Expert verified
The 90% confidence interval for the population proportion who agree with the statement is calculated from the percentiles of the bootstrap distribution, generated using a sample proportion of 112/400, as computed from the provided data.

Step by step solution

01

Calculate Sample Proportion

Firstly, calculate the sample proportion (p˂), by dividing the number of people who agree (112) by the total sample size (400). This will give the point estimate of the population proportion.
02

Implement the Bootstrap Method

Next, implement the bootstrap method using a statistical software like StatKey. Select the option for 'CI for Single Proportion', and feed in the data of the sample. Then generate a bootstrap distribution by simulating many samples of the same size as the original sample, and calculating the proportion for each.
03

Compute the Confidence Interval

Finally, compute the 90% confidence interval using the percentiles from the bootstrap distribution. To find the 90% confidence interval, identify the 5th and 95th percentile of the bootstrap distribution, which give the lower and upper limits of the confidence interval.

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Most popular questions from this chapter

Exercises 3.71 to 3.73 consider the question (using fish) of whether uncommitted members of a group make it more democratic. It has been argued that individuals with weak preferences are particularly vulnerable to a vocal opinionated minority. However, recent studies, including computer simulations, observational studies with humans, and experiments with fish, all suggest that adding uncommitted members to a group might make for more democratic decisions by taking control away from an opinionated minority. \({ }^{36}\) In the experiment with fish, golden shiners (small freshwater fish who have a very strong tendency to stick together in schools) were trained to swim toward either yellow or blue marks to receive a treat. Those swimming toward the yellow mark were trained more to develop stronger preferences and became the fish version of individuals with strong opinions. When a minority of five opinionated fish (wanting to aim for the yellow mark) were mixed with a majority of six less opinionated fish (wanting to aim for the blue mark), the group swam toward the minority yellow mark almost all the time. When some untrained fish with no prior preferences were added, however, the majority opinion prevailed most of the time. \({ }^{37}\) Exercises 3.71 to 3.73 elaborate on this study. What Is the Effect of Including Some Indifferent Fish? In the experiment described above under Fish Democracies, the schools of fish in the study with an opinionated minority and a less passionate majority picked the majority option only about \(17 \%\) of the time. However, when groups also included 10 fish with no opinion, the schools of fish picked the majority option \(61 \%\) of the time. We want to estimate the effect of adding the fish with no opinion to the group, which means we want to estimate the difference in the two proportions. We learn from the study that the standard error for estimating this difference is about \(0.14 .\) Define the parameter we are estimating, give the best point estimate, and find and interpret a \(95 \%\) confidence interval. Is it plausible that adding indifferent fish really has no effect on the outcome?

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