In: Statistics and Probability
Access the CallCenterWaitingTime.xlsx file. Each row in the database corresponds to a different call. The column variables are as follows:
QueueTime | service time |
PE |
43 |
976 |
PE |
151 |
33 |
PE |
57 |
35 |
PE |
715 |
39 |
PE |
45 |
41 |
PE |
97 |
43 |
PE |
239 |
43 |
PE |
33 |
48 |
PE |
31 |
48 |
PE |
299 |
49 |
PE |
27 |
50 |
PE |
189 |
50 |
PE |
51 |
51 |
PE |
71 |
52 |
PE |
57 |
56 |
The hypothesis being tested is:
H0: µ = 150
Ha: µ < 150
150.000 | hypothesized value |
140.333 | mean QueueTime |
179.497 | std. dev. |
46.346 | std. error |
15 | n |
14 | df |
-0.209 | t |
.4189 | p-value (one-tailed, lower) |
The p-value is 0.4189.
Since the p-value (0.4189) is greater than the significance level (0.05), we fail to reject the null hypothesis.
Therefore, we cannot conclude that the average TiQ is lower than the industry standard of 2.5 minutes (150 seconds).
The company should not allocate more resources to improve its average TiQ
There is no group named "PT". So, this test cannot be performed.