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Please stop asking for a revision. This is the entire thing I need help with. Someone answered it before but did it wrong. It is

Please stop asking for a revision. This is the entire thing I need help with. Someone answered it before but did it wrong. It is not between Atlanta and St. Louis. It is just Atlanta as seen in the first paragraph.

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When you use StatKey, include all relevant output and clearly identify your final answer by writing a sentence (e.g., "The 95% confidence interval is [XX, XX]"). Round all answers to 3 decimal places unless otherwise specified. The following questions are related to the proportion of registered voters who said they were planning to vote for "Candidate A" in the presidential election. 1. In a random sample of 20 voters, 12 said they were planning to vote for Candidate A and 8 said they were not planning to vote for Candidate A. Use StatKey to construct a 95% bootstrap confidence interval using the percentile method to estimate the proportion of all registered voters in the population who are planning to vote for Candidate A. You can enter the sample data into StatKey using the "Edit Data" button. Remember to take at least 5,000 resamples. Don't forget to include a screenshot from StatKey and to clearly identify your answer. 2. Interpret the meaning of the confidence interval constructed in question 1 by completing the phrase below. "I am 95% confident... 3. Given your confidence interval in question 1, is there evidence that the proportion of all registered voters in the population who are planning to vote for Candidate A is different from 0.50 (i.e., half)? Explain why or why not. 4. What if the sample size were 10 times bigger? Find the confidence interval if we had a sample where 120 out of 200 participants were planning to vote for Candidate A. Use StatKey to construct a 95% confidence interval using the percentile method with these new data (x=120, n=200). Take at least 5,000 resamples. Don't forget to upload a screenshot from StatKey and to clearly identify your answer. 5. When the sample size was increased, how did the standard error and width of the confidence interval change? "When the sample size increased, the standard error.. "When the sample size increased, the width of the confidence interval. 6. Using the dataset with 120 out of 200 participants planning to vote for Candidate A, construct a 90% confidence interval in StatKey using the percentile method. Take at least 5,000 resamples. Don't forget to include a screenshot from StatKey and to clearly identify your answer. 7. When the confidence level was changed from 95% to 90%, how did the standard error and width of the confidence interval change? "When the confidence level decreased, the standard error... "When the confidence level decreased, the width of the confidence interval...In this question set you will use the "Atlanta Commute (Distance)" dataset that is built into Statkey to construct bootstrap confidence intervals to estimate the mean commute distance in the population of all Atlanta commuters. These data were collected from a random sample of 500 commuters in Atlanta, Georgia. 1. Using the percentile method, construct a 95% confidence interval to estimate the mean commute distance in Atlanta. Take at least 5,000 resamples. Include a screenshot of your bootstrap sampling distribution from Statkey showing your confidence interval and clearly identify your answer. 2. Describe the shape of your bootstrap distribution from part A. Is it normally distributed or skewed? 3. Using the standard error method, construct a 95% confidence interval for mean commute distance in Atlanta. You can use the standard error from the bootstrap distribution you constructed in part A. Show all your calculations. 4. Your 95% confidence intervals in parts A and C should be similar, but they probably won't be exactly the same. Explain why the confidence intervals you constructed using the percentile method and the standard error method are not exactly the same. In other words, why may we expect answers in parts A and C to be slightly different

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