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Use the results from a survey of a simple random sample of 1182 adults. Among the 1182 respondents, 71% rated themselves as above average drivers. We want to test the claim that more than of adults rate themselves as above average drivers. Complete parts (a) through (e). a. Regardless of the conclusion reached from the hypothesis test, is it possible that more than of adults can be above average drivers? OA. No. Assuming quality of driving can be quantified, half of all adults must have driving quality less than or equal to the mean. OB. Yes. Assuming quality of driving can be quantified, a distribution that is extremely skewed to the right would be the most promising scenario for more than this proportion of adults to have driving quality that is above the mean. c. Yes. Assuming quality of driving can be quantified, a distribution that is extremely skewed to the left would be the most promising scenario for more than this proportion of adults to have driving quality that is above the mean. OD. No. It is impossible to compare the quality of different adults' driving. b. If we use the same significance level to conduct the hypothesis test using the P-value method, the critical value method, and a confidence interval, which method is not always equivalent to the other two? OA. The P-value method is not always equivalent to the other two. B. The confidence interval method is not always equivalent to the other two. OC. The critical value method is not always equivalent to the other two. O D. All three methods are always equivalent to each other. c. It was stated that we can easily remember how to interpret P-values with this: "If the P is low, the null must go." What does this mean? This statement means that if the is low in relation to then one should the

Use the results from a survey of a simple random sample of 1182 adults. Among the 1182 respondents, 71% rated themselves as above average drivers. We want to test the claim that more than of adults rate themselves as above average drivers. Complete parts (a) through (e). a. Regardless of the conclusion reached from the hypothesis test, is it possible that more than of adults can be above average drivers? OA. No. Assuming quality of driving can be quantified, half of all adults must have driving quality less than or equal to the mean. OB. Yes. Assuming quality of driving can be quantified, a distribution that is extremely skewed to the right would be the most promising scenario for more than this proportion of adults to have driving quality that is above the mean. c. Yes. Assuming quality of driving can be quantified, a distribution that is extremely skewed to the left would be the most promising scenario for more than this proportion of adults to have driving quality that is above the mean. OD. No. It is impossible to compare the quality of different adults' driving. b. If we use the same significance level to conduct the hypothesis test using the P-value method, the critical value method, and a confidence interval, which method is not always equivalent to the other two? OA. The P-value method is not always equivalent to the other two. B. The confidence interval method is not always equivalent to the other two. OC. The critical value method is not always equivalent to the other two. O D. All three methods are always equivalent to each other. c. It was stated that we can easily remember how to interpret P-values with this: "If the P is low, the null must go." What does this mean? This statement means that if the is low in relation to then one should the

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Use the results from a survey of a simple random sample of 1182 adults. Among the 1182 respondents, 71% rated themselves as above average drivers. We want to test the claim that more than \(\frac{3}{5}\) of adults rate themselves as above average drivers. Complete parts (a) through (c). a. Regardless of the conclusion reached from the hypothesis test, is it possible that more than \(\frac{3}{5}\) of adults can be above average drivers? - O A. No. Assuming quality of driving can be quantified, half of all adults must have driving quality less than or equal to the mean. - O B. Yes. Assuming quality of driving can be quantified, a distribution that is extremely skewed to the right would be the most promising scenario for more than this proportion of adults to have driving quality that is above the mean. - ● C. Yes. Assuming quality of driving can be quantified, a distribution that is extremely skewed to the left would be the most promising scenario for more than this proportion of adults to have driving quality that is above the mean. - O D. No. It is impossible to compare the quality of different adults’ driving. b. If we use the same significance level to conduct the hypothesis test using the P-value method, the critical value method, and a confidence interval, which method is not always equivalent to the other two? - O A. The P-value method is not always equivalent to the other two. - ● B. The confidence interval method is not always equivalent to the other two. - O C. The critical value method is not always equivalent to the other two. - O D. All three methods are always equivalent to each other. c. It was stated that we can easily remember how to interpret P-values with this: "If the P is low, the null must go." What does this mean? This statement means that if the \(\text{P-value}\) is low in relation to \(\text{the significance level}\) then one should \(\text{reject}\) the \(\text{null hypothesis}\).
Transcribed Image Text:Use the results from a survey of a simple random sample of 1182 adults. Among the 1182 respondents, 71% rated themselves as above average drivers. We want to test the claim that more than \(\frac{3}{5}\) of adults rate themselves as above average drivers. Complete parts (a) through (c). a. Regardless of the conclusion reached from the hypothesis test, is it possible that more than \(\frac{3}{5}\) of adults can be above average drivers? - O A. No. Assuming quality of driving can be quantified, half of all adults must have driving quality less than or equal to the mean. - O B. Yes. Assuming quality of driving can be quantified, a distribution that is extremely skewed to the right would be the most promising scenario for more than this proportion of adults to have driving quality that is above the mean. - ● C. Yes. Assuming quality of driving can be quantified, a distribution that is extremely skewed to the left would be the most promising scenario for more than this proportion of adults to have driving quality that is above the mean. - O D. No. It is impossible to compare the quality of different adults’ driving. b. If we use the same significance level to conduct the hypothesis test using the P-value method, the critical value method, and a confidence interval, which method is not always equivalent to the other two? - O A. The P-value method is not always equivalent to the other two. - ● B. The confidence interval method is not always equivalent to the other two. - O C. The critical value method is not always equivalent to the other two. - O D. All three methods are always equivalent to each other. c. It was stated that we can easily remember how to interpret P-values with this: "If the P is low, the null must go." What does this mean? This statement means that if the \(\text{P-value}\) is low in relation to \(\text{the significance level}\) then one should \(\text{reject}\) the \(\text{null hypothesis}\).
### Transcription of Educational Content **Section d:** Another memory trick sometimes used is this: "If the P is high, the null will fly." Given that a hypothesis test never results in a conclusion of proving or supporting a null hypothesis, how is this memory trick misleading? - **A.** This statement seems to suggest that with a high P-value, the alternative hypothesis has been rejected, but this conclusion cannot be made. - **B.** This statement seems to suggest that with a high P-value, the null hypothesis has been proven or is supported, but this conclusion cannot be made. - **C.** This statement seems to suggest that with a low P-value, the null hypothesis has been proven or is supported, but this conclusion cannot be made. - **D.** This statement seems to suggest that with a high P-value, the alternative hypothesis has been proven or is supported, but this conclusion cannot be made. **Section e:** Common significance levels are 0.10 and 0.05. Why would it be unwise to use a significance level with a number like 0.0563? - **A.** Using a significance level to more decimal places makes calculations of P-values more difficult. - **B.** A significance level with more than 2 decimal places has no meaning. - **C.** Choosing a more specific significance level makes it more difficult to reject the null hypothesis. - **D.** Choosing such a specific significance level could give the impression that the significance level was carefully chosen to reach a desired conclusion. ### Explanation of Diagrams **There are no diagrams or graphs in the provided text.**
Transcribed Image Text:### Transcription of Educational Content **Section d:** Another memory trick sometimes used is this: "If the P is high, the null will fly." Given that a hypothesis test never results in a conclusion of proving or supporting a null hypothesis, how is this memory trick misleading? - **A.** This statement seems to suggest that with a high P-value, the alternative hypothesis has been rejected, but this conclusion cannot be made. - **B.** This statement seems to suggest that with a high P-value, the null hypothesis has been proven or is supported, but this conclusion cannot be made. - **C.** This statement seems to suggest that with a low P-value, the null hypothesis has been proven or is supported, but this conclusion cannot be made. - **D.** This statement seems to suggest that with a high P-value, the alternative hypothesis has been proven or is supported, but this conclusion cannot be made. **Section e:** Common significance levels are 0.10 and 0.05. Why would it be unwise to use a significance level with a number like 0.0563? - **A.** Using a significance level to more decimal places makes calculations of P-values more difficult. - **B.** A significance level with more than 2 decimal places has no meaning. - **C.** Choosing a more specific significance level makes it more difficult to reject the null hypothesis. - **D.** Choosing such a specific significance level could give the impression that the significance level was carefully chosen to reach a desired conclusion. ### Explanation of Diagrams **There are no diagrams or graphs in the provided text.**
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