(Intercept) -1681. 093 25865.460 -0. 065 0. 948 -53745.563 50383.377 Living_Area 74. 157 11.951 0. 697 6. 205 000. 0 50 . 100 98 . 214 Bathrooms 18169.528 14209 . 664 0. 156 1.279 0. 207 -10433 . 043 46772 . 099 House_Age -114. 213 209 . 080 -0. 052 -0.546 0. 588 -535 . 068 306 . 643 Based on this output, fill in the blanks. The estimated beta coefficient for Living Area, b1 = Looking at the P-values (Sig column) for this model with three variables, what do you conclude about the variable Living Area (Living_Area) if a (cutoff value) = 0.05? Choose numbers of ALL correct choices in numerical order (lowest to highest). 1. The beta coefficient for Living Area is significantly different from zero. 2. The beta coefficient for Living Area is not significantly different from zero. 3. Living Area is useful in helping explain variability in the selling prices of these houses. 4. Living Area is not useful in helping explain variability in the selling prices of these houses. 5. Living Area should remain in the model. 6. Living Area should not remain in the model