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In this problem, assume that the distribution of differences is approximately normal. Note: For degrees of...

In this problem, assume that the distribution of differences is approximately normal. Note: For degrees of freedom d.f. not in the Student's t table, use the closest d.f. that is smaller. In some situations, this choice of d.f. may increase the P-value by a small amount and therefore produce a slightly more "conservative" answer. Are America's top chief executive officers (CEOs) really worth all that money? One way to answer this question is to look at row B, the annual company percentage increase in revenue, versus row A, the CEO's annual percentage salary increase in that same company. Suppose a random sample of companies yielded the following data: B: Percent increase for company 28 6 8 18 6 4 21 37 A: Percent increase for CEO 27 22 14 14 -4 19 15 30 Do these data indicate that the population mean percentage increase in corporate revenue (row B) is different from the population mean percentage increase in CEO salary? Use a 5% level of significance. Solve the problem using the critical region method of testing. (Let d = B − A. Round your answers to three decimal places.) test statistic = critical value = ± Interpret your conclusion in the context of the application. Reject the null hypothesis, there is sufficient evidence to claim a difference in population mean percentage increases for corporate revenue and CEO salary. Reject the null hypothesis, there is insufficient evidence to claim a difference in population mean percentage increases for corporate revenue and CEO salary. Fail to reject the null hypothesis, there is insufficient evidence to claim a difference in population mean percentage increases for corporate revenue and CEO salary. Fail to reject the null hypothesis, there is sufficient evidence to claim a difference in population mean percentage increases for corporate revenue and CEO salary. Compare your conclusion with the conclusion obtained by using the P-value method. Are they the same? We reject the null hypothesis using the P-value method, but fail to reject using the critical region method. The conclusions obtained by using both methods are the same. We reject the null hypothesis using the critical region method, but fail to reject using the P-value method.

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