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TABLE 10-14
a Problem with a Telephone Line That Prevents

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TABLE 10-14
A problem with a telephone line that prevents a customer from receiving or making calls is disconcerting to both the customer and the telephone company. The data on samples of 20 problems reported to two different offices of a telephone company and the time to clear these problems (in minutes) from the customers' lines are collected. Below is the Excel output to see whether there is evidence of a difference in the mean waiting time between the two offices assuming that the population variances in the two offices are not equal.
 t- Test: Two- Sample Assuming Unequal Variances  Office 1  Office 2  Mean 22142.0115 Variance 2.9516573.57855 Observations 2020 Hypothesized Mean Difference 0df38t Stat 0.354386P(T<=t) one- tail 0.362504t Critical one- tail 1.685953P(T<=t) two- tail 0.725009t Critical two- tail 2.024394\begin{array}{l}\text { t- Test: Two- Sample Assuming Unequal Variances }\\\begin{array} { l r r } \hline & \text { Office 1 } & \text { Office 2 } \\\hline \text { Mean } & 2214 & 2.0115 \\\text { Variance } & 2.951657 & 3.57855 \\\text { Observations } & 20 & 20 \\\text { Hypothesized Mean Difference } & 0 & \\\mathrm { df } & 38 & \\\mathrm { t } \text { Stat } & 0.354386 & \\\mathrm { P } ( \mathrm { T } < = \mathrm { t } ) \text { one- tail } & 0.362504 & \\\mathrm { t } \text { Critical one- tail } & 1.685953 & \\\mathrm { P } ( \mathrm { T } < = \mathrm { t } ) \text { two- tail } & 0.725009 & \\\mathrm { t } \text { Critical two- tail } & 2.024394 &\end{array}\end{array}
-Referring to Table 10-14, what is the 95% confidence interval estimate for the difference in the two means if the two population variances are assumed to be the same?


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