A Professional Employee in a Large Corporation Receives an Average $\mu$

Multiple Choice

A professional employee in a large corporation receives an average of $\mu$ = 38.9 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 31 employees showed that they were receiving an average of x = 30.1 e-mails per day. The computer server through which the e-mails are routed showed that $\sigma$ = 19.4. Has the new policy had any effect? Use a 10% 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 $\alpha$ ? Based on your answers, will you reject or fail to reject the null hypothesis?

A) The P-value is greater than than the level of significance and so the data are not statistically significant. Thus, we reject the null hypothesis.
B) The P-value is greater than than the level of significance and so the data are statistically significant. Thus, we reject the null hypothesis.
C) The P-value is less than than the level of significance and so the data are statistically significant. Thus, we reject the null hypothesis.
D) The P-value is less than than the level of significance and so the data are not statistically significant. Thus, we fail to reject the null hypothesis.
E) The P-value is greater than than the level of significance and so the data are statistically significant. Thus, we fail to reject the null hypothesis.