Out of the two models in Output 2 Model 1 has just locID and mktsize, Model 2 has an additional interaction term. Write out Model 1 in the regression in the form of estimated y (of the form that = a+ bx).

Regression Assignment For all Questions, use OUTPUT. Note: In Model 2 the Int variable is on interaction between mktsize and locid (i.e., Int = mktsize * locid) Variables Entered/Removed" Model Summary Variables | Variables Std. Error Model Entered Removed Method Adjusted of the locid Enter Model R R Square R Square Estimate mktsize 567 0.321 0.319 8.46674 int Enter 2 655 0.428 0.425 7.77764 a. Dependent Variable: sales a. Predictors: (Constant), locid, mktsize b. All requested variables entered. b. Predictors: (Constant), locid, mktsize, int ANOVA" Sum of Mean Model Squares Square F Sig. Regression 17954.591 2 8977.295 125.231 .0DO Residual 37921.692 529 71.686 Total 55876.283 531 2 Regression 23936.708 3 7978.903 131.901 000 Residual 31939.575 528 60.492 Total 55876.283 531 a. Dependent Variable: sales Units sold in thousands b. Predictors: (Constant), locid, mktsize C. Predictors: (Constant), locid, mktsize, int Coefficients Unstandardized Standardized Coefficients Coefficients Model B Sid. Error Batz t Sig. (Constant) 56.969 1.578 36.102 0.000 mktsize 1.602 0.500 0.119 3.204 D.001 locid -1.809 0.128 0.523 -14.082 D.DO0 2 (Constant) 25.718 3.461 7.431 0.000 mktsize 12.978 1.233 0.965 10.528 0.000 locid 3.199 0.517 0.926 6.185 0.DO0 Int -1.862 0.187 -1.506 -9.944 0.000 a. Dependent Variable: sales b. interaction between mkisize and locid (mktsize locid)