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

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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 13-9,the error sum of squares (SSE) of the above regression is A) 1.878215 B) 92.0325465 C) 335.047257 D) 427.079804
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 13-9,the error sum of squares (SSE) of the above regression is A) 1.878215 B) 92.0325465 C) 335.047257 D) 427.079804
Note: 2.051 E - 05 = 2.051*10-5 and 5.944 E -18 = 5.944 *10 -18 .
-Referring to Scenario 13-9,the error sum of squares (SSE) of the above regression is


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