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*_{1} + 1.28 *Q*_{2} + 0.617 *Q*_{3}

where

Y 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*_{1} is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise

*Q*_{2} is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise

*Q*_{3} is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise

The best interpretation of the constant 3.37 in the regression equation is

the fitted value for the first quarter of 2010, prior to seasonal adjustment, is 10^{3.37}.

the fitted value for the first quarter of 2010, after to seasonal adjustment, is log10 3.37.

the fitted value for the first quarter of 2010, after to seasonal adjustment, is 10^{3.37}.

the fitted value for the first quarter of 2010, prior to seasonal adjustment, is log10 3.37.