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TABLE 16-13 A Local Store Developed a Multiplicative Time-Series Model to Forecast

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TABLE 16-13
A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 4-year period from 2005 to 2009. The following is the resulting regression equation:
TABLE 16-13 A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 4-year period from 2005 to 2009. The following is the resulting regression equation:        -Referring to Table 16-13, the best interpretation of the constant 6.102 in the regression equation is: A)  the fitted value for the first quarter of 2005, prior to seasonal adjustment, is log<sub>10</sub>(6.102) . B)  the fitted value for the first quarter of 2005, after seasonal adjustment, is log<sub>10</sub>(6.102) . C)  the fitted value for the first quarter of 2005, prior to seasonal adjustment, is 10<sup>6.102</sup>. D)  the fitted value for the first quarter of 2005, after seasonal adjustment, is 10<sup>6.102</sup>.
TABLE 16-13 A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 4-year period from 2005 to 2009. The following is the resulting regression equation:        -Referring to Table 16-13, the best interpretation of the constant 6.102 in the regression equation is: A)  the fitted value for the first quarter of 2005, prior to seasonal adjustment, is log<sub>10</sub>(6.102) . B)  the fitted value for the first quarter of 2005, after seasonal adjustment, is log<sub>10</sub>(6.102) . C)  the fitted value for the first quarter of 2005, prior to seasonal adjustment, is 10<sup>6.102</sup>. D)  the fitted value for the first quarter of 2005, after seasonal adjustment, is 10<sup>6.102</sup>.
-Referring to Table 16-13, the best interpretation of the constant 6.102 in the regression equation is:


Definitions:

Mean

The average of a set of numerical values, calculated by adding them together and dividing by the number of values.

Standard Deviation

A measure that quantifies the amount of variation or dispersion of a set of data values from the mean.

Normal Probability Distribution

Also known as the Gaussian distribution, it's a bell-shaped curve that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean.

Random Variables

Variables whose values depend on outcomes of a stochastic (random) phenomenon.

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