Does the presence of detached garage and presence of pool affect the home price?

Perform an ANOVA with interaction between Garage and Pool, and Price as the dependent variable.

1. According to the results, which one of the independent variables and/or their interaction significantly affect the home prices at significance level of 0.05?

Source Garage (Y*Pool (yes Residual Type 3 Analysis of Variance DF Sum of Squares Mean Square Expected Mean Square Error Term 3 436123530597 145374510199 Var(Residual) +Q(Garage (Y*Pool (yes) MS(Residual) 101 2.2496279E12 22273543716 Var(Residual) Error DF F Value Pr>F 101 6.53 0.0004 Covariance Parameter Estimates Cov Parm Estimate Alpha Lower Upper Residual 2.227E10 Fit Statistics 2 Res Log Likelihood 2705.5 AIC (Smaller is Better) 2707.5 AICC (Smaller is Better) 2707.6 BIC (Smaller is Better) 2710.1 Type 3 Tests of Fixed Effects Effect Num DF Den DF F Value Pr>F Garage (Y*Pool (yes 3 101 6.53 0.0004 Residuals for Price 0 O 40 400000 OBD 30 200000 Residual Percent 20 LOOOOO 0 DO COM O OOO OCCIDED O OCICIEL OID COD 10 -200000 0 250000 400000 -48E4 -24E4 240000 300000 350000 Predicted Mean 480000 0 Residual 400000 ac 200000 Residual Residual Statistics Observations 105 Minimum -238E3 Mean -3E-11 Maximum 513847 Std Dev 147075 Fit Statistics Objective 2705.5 AIC 2707.5 AICC 2707.6 BIC 2710.1 -200000 oooooo -400000 -2 -1 1 N 0 Quantile Source Garage (Y*Pool (yes Residual Type 3 Analysis of Variance DF Sum of Squares Mean Square Expected Mean Square Error Term 3 436123530597 145374510199 Var(Residual) +Q(Garage (Y*Pool (yes) MS(Residual) 101 2.2496279E12 22273543716 Var(Residual) Error DF F Value Pr>F 101 6.53 0.0004 Covariance Parameter Estimates Cov Parm Estimate Alpha Lower Upper Residual 2.227E10 Fit Statistics 2 Res Log Likelihood 2705.5 AIC (Smaller is Better) 2707.5 AICC (Smaller is Better) 2707.6 BIC (Smaller is Better) 2710.1 Type 3 Tests of Fixed Effects Effect Num DF Den DF F Value Pr>F Garage (Y*Pool (yes 3 101 6.53 0.0004 Residuals for Price 0 O 40 400000 OBD 30 200000 Residual Percent 20 LOOOOO 0 DO COM O OOO OCCIDED O OCICIEL OID COD 10 -200000 0 250000 400000 -48E4 -24E4 240000 300000 350000 Predicted Mean 480000 0 Residual 400000 ac 200000 Residual Residual Statistics Observations 105 Minimum -238E3 Mean -3E-11 Maximum 513847 Std Dev 147075 Fit Statistics Objective 2705.5 AIC 2707.5 AICC 2707.6 BIC 2710.1 -200000 oooooo -400000 -2 -1 1 N 0 Quantile