During 2013 a company implemented a number of policies aimed at reducing the ages of its customers€™ accounts. In order to assess the effectiveness of these measures, the company randomly selects 10 customer accounts. The average age of each account is determined for the years 2012 and 2013. These data are given in Table 10.4. Assuming that the population of paired differences between the average ages in 2013 and 2012 is normally distributed:

a. Set up the null and alternative hypotheses needed to establish that the mean average account age has been reduced by the company€™s new policies.
b. Figure 10.10 gives the Excel output needed to test the hypotheses of part a. Use critical values to test these hypotheses by setting α equal to .10, .05, .01, and .001. How much evidence is there that the mean average account age has been reduced?

c. Figure 10.10 gives the p- value for testing the hypotheses of part a. Use the p-value to test these hypotheses by setting α equal to .10, .05, .01, and .001. How much evidence is there that the mean average account age has been reduced?
d. Calculate a 95 percent confidence interval for the mean difference in the average account ages between 2013 and 2012. Estimate the minimum reduction in the mean average account ages from 2012 to 2013.

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Average Age of Account in 2013 Average Age of Account in 2012 (Days) 35 24 47 28 41 Account (Days) 27 19 40 30 25 31 29 15 21 35 51 18 28 10 t-Test: Paired Two Sample for Means 2013 Age 27 53.55556 10 0.804586 2012 Age 34 104.2222 10 Mean Variance Observations Pearson Correlation Hypothesized Mean df t Stat P(T<-t) one-tail t Critical one-tail P(T