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A professional employee in a large corporation receives an average of u=40 e-mails per day. Most...

A professional employee in a large corporation receives an average of u=40 e-mails per day. Most of these e-mails are from other employees in the company. Because of the large number of e-mails, employees find themselves distracted and are unable to concentrate when they return to their tasks. In an effort to reduce distraction caused by such interruptions, one company established a priority list that all employees were to use before sending an e-mail. One month after the new priority list was put into place, a random sample of 33 employees showed that they were receiving an average of Xbar=33.4 e-mails per day. The computer server through which the e-mails are routed showed that o=17.5. Use a 5% level of significance to test the claim that there has been a change (either way) in the average number of e-mails received per day per employee. Are the data statistically significant at level α? Based on your answers, will you reject or fail to reject the null hypothesis?

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The P-value is greater than the level of significance and so the data are not statistically significant. Thus, we reject the null hypothesis.

The P-value is greater than the level of significance and so the data are statistically significant. Thus, we fail to reject the null hypothesis.

The P-value is less than the level of significance and so the data are statistically significant. Thus, we reject the null hypothesis.

The P-value is greater than the level of significance and so the data are not statistically significant. Thus, we fail to reject the null hypothesis.

The P-value is greater than the level of significance and so the data are statistically significant. Thus, we reject the null hypothesis.

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