The management of a chain electronic store would like to develop a model for predicting the weekly sales (in thousand of dollars) for individual stores based on the number of customers who made purchases. A random sample of 12 stores yields the following results: Sales (Thousands of Dollars) Customers 907 11.20 926 11.05 713 8.21 741 9.21 780 9.42 898 10.08 510 6.73 529 7.02 460 6.12 872 9.52 650 7.53 603 7.25 True or False: Referring to Table 12-10, the null hypothesis for testing whether the number of customers who make a purchase effects weekly sales cannot be rejected if a 1% probability of committing a Type I error is desired. Select one: O True O Fake

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TABLE 12-10
The management of a chain electronic store would like to develop a
model for predicting the weekly sales (in thousand of dollars) for
individual stores based on the number of customers who made
purchases. A random sample of 12 stores yields the following results:
Sales (Thousands of
Customers
Dollars)
907
11.20
926
11.05
713
8.21
741
9.21
780
9.42
898
10.08
510
6.73
529
7.02
460
6.12
872
9.52
650
7.53
603
7.25
True or False: Referring to Table 12-10, the nulI hypothesis for testing
whether the number of customers who make a purchase effects weekly
sales cannot be rejected if a 1% probability of committing a Type I error is
desired.
Select one:
O True
O Fake
Transcribed Image Text:TABLE 12-10 The management of a chain electronic store would like to develop a model for predicting the weekly sales (in thousand of dollars) for individual stores based on the number of customers who made purchases. A random sample of 12 stores yields the following results: Sales (Thousands of Customers Dollars) 907 11.20 926 11.05 713 8.21 741 9.21 780 9.42 898 10.08 510 6.73 529 7.02 460 6.12 872 9.52 650 7.53 603 7.25 True or False: Referring to Table 12-10, the nulI hypothesis for testing whether the number of customers who make a purchase effects weekly sales cannot be rejected if a 1% probability of committing a Type I error is desired. Select one: O True O Fake
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