Question: Table 1 A problem with a phone line that prevents a customer from receiving or making calls is upsetting to both the customer and the

 Table 1 A problem with a phone line that prevents a
customer from receiving or making calls is upsetting to both the customer
and the telecommunications company. The file "Phone" contains samples of 20 problems

Table 1 A problem with a phone line that prevents a customer from receiving or making calls is upsetting to both the customer and the telecommunications company. The file "Phone" contains samples of 20 problems reported to two different offices of a telecommunications company and the time to clear these problems (in minutes) from the customers' lines: Central Office I Time to Clear Problems (minutes) 1.48 1.75 0.78 2.85 0.52 1.60 4.15 3.97 1.48 3.10 1.020.53 0.93 1.60 0.80 1.05 6.32 3.93 5.45 0.97 Central Office II Time to Clear Problems (minutes) 7.55 3.75 0.10 1.10 0.60 0.52 3.30 2.10 0.58 4.02 3.75 0.65 1.92 0.60 1.53 4.23 0.08 1.48 1.650.72 Assuming that the population variances from both offices are equal, is there evidence of a difference in the mean waiting time between the two offices? (Use a = 0.10.) You need to download file Phone". 1 E G BCD 1 rimelocation 2 1.48 3 1.75 1 4 0.78 1 5 2.85 1 6 0.52 1 7 1.60 1 8 4.15 1 9 3.97 1 10 1.48 1 11 3.10 1 12 1.02 13 0.53 1 14 0.93 1 15 1.60 1 16 0.80 1 17 1.05 1 18 6.32 1 19 3.93 1 20 5.45 1 21 0.97 1 22 7.55 23 3.75 24 0.10 25 1.10 26 0.60 27 0.52 28 3.30 29 2.10 30 0.58 31 4.02 2 32 3.75 33 0.65 34 1.92 2 35 0.60 36 153 ST 423 38 0.08 38 1.48 40 1.65 41 0.72 42 43 44 45 46 47 NNNNNNNNN NN NNNNNNN Question 24 (3 points) Referring to Table 1, judging from the way the data were collected, which test would likely be most appropriate to employ? 1) Separate-variance t test for the difference between two means O2) Ftest for the ratio of two variances 3) Paired t test 4) Pooled-variance t test for the difference between two means Table 1 A problem with a phone line that prevents a customer from receiving or making calls is upsetting to both the customer and the telecommunications company. The file "Phone" contains samples of 20 problems reported to two different offices of a telecommunications company and the time to clear these problems (in minutes) from the customers' lines: Central Office I Time to Clear Problems (minutes) 1.48 1.75 0.78 2.85 0.52 1.60 4.15 3.97 1.48 3.10 1.020.53 0.93 1.60 0.80 1.05 6.32 3.93 5.45 0.97 Central Office II Time to Clear Problems (minutes) 7.55 3.75 0.10 1.10 0.60 0.52 3.30 2.10 0.58 4.02 3.75 0.65 1.92 0.60 1.53 4.23 0.08 1.48 1.650.72 Assuming that the population variances from both offices are equal, is there evidence of a difference in the mean waiting time between the two offices? (Use a = 0.10.) You need to download file Phone". 1 E G BCD 1 rimelocation 2 1.48 3 1.75 1 4 0.78 1 5 2.85 1 6 0.52 1 7 1.60 1 8 4.15 1 9 3.97 1 10 1.48 1 11 3.10 1 12 1.02 13 0.53 1 14 0.93 1 15 1.60 1 16 0.80 1 17 1.05 1 18 6.32 1 19 3.93 1 20 5.45 1 21 0.97 1 22 7.55 23 3.75 24 0.10 25 1.10 26 0.60 27 0.52 28 3.30 29 2.10 30 0.58 31 4.02 2 32 3.75 33 0.65 34 1.92 2 35 0.60 36 153 ST 423 38 0.08 38 1.48 40 1.65 41 0.72 42 43 44 45 46 47 NNNNNNNNN NN NNNNNNN Question 24 (3 points) Referring to Table 1, judging from the way the data were collected, which test would likely be most appropriate to employ? 1) Separate-variance t test for the difference between two means O2) Ftest for the ratio of two variances 3) Paired t test 4) Pooled-variance t test for the difference between two means

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