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SCENARIO 16-12 a Local Store Developed a Multiplicative Time-Series Model

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SCENARIO 16-12 A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 5-year period from 2009 to 2013.The following is the resulting regression equation: SCENARIO 16-12 A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 5-year period from 2009 to 2013.The following is the resulting regression equation:   where   is the estimated number of contracts in a quarter. X is the coded quarterly value with X = 0 in the first quarter of 2008.   is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.   is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise.   is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise. -Referring to Scenario 16-12, the best interpretation of the constant 6.102 in the regression equation is: A) the fitted value for the first quarter of 2009, prior to seasonal adjustment, is   6.102) . B) the fitted value for the first quarter of 2009, after to seasonal adjustment, is   (6.102) . C) the fitted value for the first quarter of 2009, prior to seasonal adjustment, is   D) the fitted value for the first quarter of 2009, after to seasonal adjustment, is  where SCENARIO 16-12 A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 5-year period from 2009 to 2013.The following is the resulting regression equation:   where   is the estimated number of contracts in a quarter. X is the coded quarterly value with X = 0 in the first quarter of 2008.   is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.   is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise.   is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise. -Referring to Scenario 16-12, the best interpretation of the constant 6.102 in the regression equation is: A) the fitted value for the first quarter of 2009, prior to seasonal adjustment, is   6.102) . B) the fitted value for the first quarter of 2009, after to seasonal adjustment, is   (6.102) . C) the fitted value for the first quarter of 2009, prior to seasonal adjustment, is   D) the fitted value for the first quarter of 2009, after to seasonal adjustment, is  is the estimated number of contracts in a quarter. X is the coded quarterly value with X = 0 in the first quarter of 2008. SCENARIO 16-12 A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 5-year period from 2009 to 2013.The following is the resulting regression equation:   where   is the estimated number of contracts in a quarter. X is the coded quarterly value with X = 0 in the first quarter of 2008.   is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.   is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise.   is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise. -Referring to Scenario 16-12, the best interpretation of the constant 6.102 in the regression equation is: A) the fitted value for the first quarter of 2009, prior to seasonal adjustment, is   6.102) . B) the fitted value for the first quarter of 2009, after to seasonal adjustment, is   (6.102) . C) the fitted value for the first quarter of 2009, prior to seasonal adjustment, is   D) the fitted value for the first quarter of 2009, after to seasonal adjustment, is  is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise. SCENARIO 16-12 A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 5-year period from 2009 to 2013.The following is the resulting regression equation:   where   is the estimated number of contracts in a quarter. X is the coded quarterly value with X = 0 in the first quarter of 2008.   is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.   is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise.   is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise. -Referring to Scenario 16-12, the best interpretation of the constant 6.102 in the regression equation is: A) the fitted value for the first quarter of 2009, prior to seasonal adjustment, is   6.102) . B) the fitted value for the first quarter of 2009, after to seasonal adjustment, is   (6.102) . C) the fitted value for the first quarter of 2009, prior to seasonal adjustment, is   D) the fitted value for the first quarter of 2009, after to seasonal adjustment, is  is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise. SCENARIO 16-12 A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 5-year period from 2009 to 2013.The following is the resulting regression equation:   where   is the estimated number of contracts in a quarter. X is the coded quarterly value with X = 0 in the first quarter of 2008.   is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.   is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise.   is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise. -Referring to Scenario 16-12, the best interpretation of the constant 6.102 in the regression equation is: A) the fitted value for the first quarter of 2009, prior to seasonal adjustment, is   6.102) . B) the fitted value for the first quarter of 2009, after to seasonal adjustment, is   (6.102) . C) the fitted value for the first quarter of 2009, prior to seasonal adjustment, is   D) the fitted value for the first quarter of 2009, after to seasonal adjustment, is  is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise.
-Referring to Scenario 16-12, the best interpretation of the constant 6.102 in the regression equation is:


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