Instruction 14-5
a Local Store Developed a Multiplicative Time-Series Model $\hat { Y }$

Instruction 14-5
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:
log 10 $\hat { Y }$ = 6.102 + 0.012 X - 0.129 Q₁ - 0.054 Q₂ + 0.098 Q₃
Where
$\hat { Y }$ is the estimated number of contracts in a quarter
X is the coded quarterly value with X = 0 in the first quarter of 2005.
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 Instruction 14-5,the best interpretation of the coefficient of Q₃ (0.098) in the regression equation is

A) the revenues in the third quarter of a year is approximately 25.31% higher than the average over all 4 quarters.
B) the revenues in the third quarter of a year is approximately 25.31% higher than it would be during the fourth quarter.
C) the revenues in the third quarter of a year is approximately 9.8% higher than the average over all 4 quarters.
D) the revenues in the third quarter of a year is approximately 9.8% higher than it would be during the fourth quarter.