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TABLE 13-12 The Manager of the Purchasing Department of a Large Banking

Question 186

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TABLE 13-12
The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of time (measured in hours) it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time in hours is recorded. Below is the regression output:
TABLE 13-12 The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of time (measured in hours) it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time in hours is recorded. Below is the regression output: Note: 4.3946E-15 is 4.3946×10<sup>-15</sup> -Referring to Table 13-12, to test the claim that the average amount of time depends positively on the number of invoices processed against the null hypothesis that the average amount of time does not depend linearly on the number of invoices processed, the p-value of the test statistic is A) (4.3946E-15) /2. B) 4.3946E-15. C) (4.3946E-15) *2. D) 0.0030. Note: 4.3946E-15 is 4.3946×10-15
TABLE 13-12 The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of time (measured in hours) it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time in hours is recorded. Below is the regression output: Note: 4.3946E-15 is 4.3946×10<sup>-15</sup> -Referring to Table 13-12, to test the claim that the average amount of time depends positively on the number of invoices processed against the null hypothesis that the average amount of time does not depend linearly on the number of invoices processed, the p-value of the test statistic is A) (4.3946E-15) /2. B) 4.3946E-15. C) (4.3946E-15) *2. D) 0.0030. TABLE 13-12 The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of time (measured in hours) it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time in hours is recorded. Below is the regression output: Note: 4.3946E-15 is 4.3946×10<sup>-15</sup> -Referring to Table 13-12, to test the claim that the average amount of time depends positively on the number of invoices processed against the null hypothesis that the average amount of time does not depend linearly on the number of invoices processed, the p-value of the test statistic is A) (4.3946E-15) /2. B) 4.3946E-15. C) (4.3946E-15) *2. D) 0.0030.
-Referring to Table 13-12, to test the claim that the average amount of time depends positively on the number of invoices processed against the null hypothesis that the average amount of time does not depend linearly on the number of invoices processed, the p-value of the test statistic is


A) (4.3946E-15) /2.
B) 4.3946E-15.
C) (4.3946E-15) *2.
D) 0.0030.

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