Answer the following question based on this situation: You run standard multiple regression on your variables (dependent Q; independents A, B, C, and D). The resulting regression output is the following:

	Coefficients	Standard Error	P-value (or Sig value)	Lower 95%	Upper 95%
Intercept	50.971	1.273	4.094E-06	524.04117	1091.796
A	- 0.625	0.061	4.341E-11	-5.9751292	-4.09374
B	0.175	0.020	5.737E-05	2.7893473	6.931397
C	0.555	0.044	4.292E-03	0.1129530	0.543153
D	- 0.0009	0.035	2.384E-08	0.0064627	0.010948

Based on the coefficient output, what is the resulting regression model to predict Q?

Q = 50.971-0.424A+0.35B+0.68C-0.001D

Q = 1.273-0.061A+0.020B+0.044C-0.035D

Q = 50.971+0.625A+0.175B+0.555C+0.0009D

Q = 50.971+(-0.625A)+0.175B+0.555C+(-0.0009D)

Q = 50.971 - 0.625 (A) + 0.175 (B) + 0.555 (C) - 0.009 (D)