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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 coefficient of   in the regression equation is: A) the revenues in the second quarter of a year is approximately 5.4% lower than the average over all 4 quarters. B) the revenues in the second quarter of a year is approximately 5.4% lower than it would be during the fourth quarter. C) the revenues in the second quarter of a year is approximately 11.69% lower than the average over all 4 quarters. D) the revenues in the second quarter of a year is approximately 11.69% lower than it would be during the fourth quarter. 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 coefficient of   in the regression equation is: A) the revenues in the second quarter of a year is approximately 5.4% lower than the average over all 4 quarters. B) the revenues in the second quarter of a year is approximately 5.4% lower than it would be during the fourth quarter. C) the revenues in the second quarter of a year is approximately 11.69% lower than the average over all 4 quarters. D) the revenues in the second quarter of a year is approximately 11.69% lower 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 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 coefficient of   in the regression equation is: A) the revenues in the second quarter of a year is approximately 5.4% lower than the average over all 4 quarters. B) the revenues in the second quarter of a year is approximately 5.4% lower than it would be during the fourth quarter. C) the revenues in the second quarter of a year is approximately 11.69% lower than the average over all 4 quarters. D) the revenues in the second quarter of a year is approximately 11.69% lower than it would be during the fourth quarter. 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 coefficient of   in the regression equation is: A) the revenues in the second quarter of a year is approximately 5.4% lower than the average over all 4 quarters. B) the revenues in the second quarter of a year is approximately 5.4% lower than it would be during the fourth quarter. C) the revenues in the second quarter of a year is approximately 11.69% lower than the average over all 4 quarters. D) the revenues in the second quarter of a year is approximately 11.69% lower than it would be during the fourth quarter. 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 coefficient of   in the regression equation is: A) the revenues in the second quarter of a year is approximately 5.4% lower than the average over all 4 quarters. B) the revenues in the second quarter of a year is approximately 5.4% lower than it would be during the fourth quarter. C) the revenues in the second quarter of a year is approximately 11.69% lower than the average over all 4 quarters. D) the revenues in the second quarter of a year is approximately 11.69% lower than it would be during the fourth quarter. 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 coefficient of 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 coefficient of   in the regression equation is: A) the revenues in the second quarter of a year is approximately 5.4% lower than the average over all 4 quarters. B) the revenues in the second quarter of a year is approximately 5.4% lower than it would be during the fourth quarter. C) the revenues in the second quarter of a year is approximately 11.69% lower than the average over all 4 quarters. D) the revenues in the second quarter of a year is approximately 11.69% lower than it would be during the fourth quarter. in the regression equation is:


Definitions:

Test Statistic

A statistic whose calculated value is used to decide whether to reject the null hypothesis in a hypothesis test.

Population Distribution

The distribution of a characteristic within an entire population, described by parameters such as mean, variance, and standard deviation.

Null Hypothesis

A hypothesis that suggests there is no statistical significance between two variables, often used as a default hypothesis in testing.

Standard Deviation

A measure of the dispersion or spread of a set of values, indicating how much the values deviate from the mean of the data.

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