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TABLE 16-14 a Contractor Developed a Multiplicative Time-Series Model to Forecast the Forecast

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TABLE 16-14
A contractor developed a multiplicative time-series model to forecast the number of contracts in future quarters,using quarterly data on number of contracts during the 3-year period from 2010 to 2012.The following is the resulting regression equation:
ln TABLE 16-14 A contractor developed a multiplicative time-series model to forecast the number of contracts in future quarters,using quarterly data on number of contracts during the 3-year period from 2010 to 2012.The following is the resulting regression equation: ln   = 3.37 + 0.117 X - 0.083 Q<sub>1</sub> + 1.28 Q<sub>2</sub> + 0.617 Q<sub>3</sub> where   is the estimated number of contracts in a quarter X is the coded quarterly value with X = 0 in the first quarter of 2010 Q<sub>1</sub> is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise Q<sub>2</sub> is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise Q<sub>3</sub> is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise -Referring to Table 16-14,the best interpretation of the coefficient of Q<sub>3</sub> (0.617) in the regression equation is A) the number of contracts in the third quarter of a year is approximately 62% higher than the average over all 4 quarters. B) the number of contracts in the third quarter of a year is approximately 62% higher than it would be during the fourth quarter. C) the number of contracts in the third quarter of a year is approximately 314% higher than the average over all 4 quarters. D) the number of contracts in the third quarter of a year is approximately 314% higher than it would be during the fourth quarter. = 3.37 + 0.117 X - 0.083 Q1 + 1.28 Q2 + 0.617 Q3
where TABLE 16-14 A contractor developed a multiplicative time-series model to forecast the number of contracts in future quarters,using quarterly data on number of contracts during the 3-year period from 2010 to 2012.The following is the resulting regression equation: ln   = 3.37 + 0.117 X - 0.083 Q<sub>1</sub> + 1.28 Q<sub>2</sub> + 0.617 Q<sub>3</sub> where   is the estimated number of contracts in a quarter X is the coded quarterly value with X = 0 in the first quarter of 2010 Q<sub>1</sub> is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise Q<sub>2</sub> is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise Q<sub>3</sub> is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise -Referring to Table 16-14,the best interpretation of the coefficient of Q<sub>3</sub> (0.617) in the regression equation is A) the number of contracts in the third quarter of a year is approximately 62% higher than the average over all 4 quarters. B) the number of contracts in the third quarter of a year is approximately 62% higher than it would be during the fourth quarter. C) the number of contracts in the third quarter of a year is approximately 314% higher than the average over all 4 quarters. D) the number of contracts in the third quarter of a year is approximately 314% higher than it would be during the fourth quarter. is the estimated number of contracts in a quarter
X is the coded quarterly value with X = 0 in the first quarter of 2010
Q1 is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise
Q2 is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise
Q3 is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise
-Referring to Table 16-14,the best interpretation of the coefficient of Q3 (0.617) in the regression equation is


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