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SCENARIO 13-9
It Is Believed That, the Average Numbers of Hours

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SCENARIO 13-9
It is believed that, the average numbers of hours spent studying per day (HOURS) during undergraduate education should have a positive linear relationship with the starting salary (SALARY, measured in thousands of dollars per month) after graduation. Given below is the Excel output for predicting starting salary (Y) using number of hours spent studying per day (X) for a sample of 51 students. NOTE: Only partial output is shown.
 SCENARIO 13-9 It is believed that, the average numbers of hours spent studying per day (HOURS) during undergraduate education should have a positive linear relationship with the starting salary (SALARY, measured in thousands of dollars per month) after graduation. Given below is the Excel output for predicting starting salary (Y) using number of hours spent studying per day (X) for a sample of 51 students. NOTE: Only partial output is shown.     Note: 2.051 E - 05 = 2.051*1<sup>0-5</sup>  and 5.944 E -18 = 5.944 *10 <sup>-18</sup> . -Referring to Scenario 13-8,the value of the measured (observed)test statistic of the F-test for H<sub>0 </sub>:  \beta <sub>1</sub>= 0 vs.H<sub>1 </sub>:  \beta <sub>1</sub> \neq  0 A)may be negative. B)is always positive. C)is always negative. D)has the same sign as the corresponding t test statistic.
 SCENARIO 13-9 It is believed that, the average numbers of hours spent studying per day (HOURS) during undergraduate education should have a positive linear relationship with the starting salary (SALARY, measured in thousands of dollars per month) after graduation. Given below is the Excel output for predicting starting salary (Y) using number of hours spent studying per day (X) for a sample of 51 students. NOTE: Only partial output is shown.     Note: 2.051 E - 05 = 2.051*1<sup>0-5</sup>  and 5.944 E -18 = 5.944 *10 <sup>-18</sup> . -Referring to Scenario 13-8,the value of the measured (observed)test statistic of the F-test for H<sub>0 </sub>:  \beta <sub>1</sub>= 0 vs.H<sub>1 </sub>:  \beta <sub>1</sub> \neq  0 A)may be negative. B)is always positive. C)is always negative. D)has the same sign as the corresponding t test statistic.
Note: 2.051 E - 05 = 2.051*10-5 and 5.944 E -18 = 5.944 *10 -18 .
-Referring to Scenario 13-8,the value of the measured (observed)test statistic of the F-test for H0 : β\beta 1= 0 vs.H1 : β\beta 1 \neq 0
A)may be negative.
B)is always positive.
C)is always negative.
D)has the same sign as the corresponding t test statistic.


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