SUMMARY OUTPUT Regression Statistics Multiple R 0.816329 R Square 0.666393 Adjusted F 0.645543 Standard 1 66.32231 Observatic 103 ANOVA df SS MS F gnificance F Regression 6 843501.5 140583.6 31.96063 7.24E-21 Residual 96 422270.3 4398.649 Total 102 1265772 Coefficientsandard Err t Stat P-value Lower 95%Upper 95%ower 95.09/pper 95.0% Intercept 12.38989 29.55027 0.419282 0.675947 -46.2669 71.04672 -46.2669 71.04672 bedrooms -7.69255 11.44394 -0.67219 0.503075 -30.4086 15.0235 -30.4086 15.0235 garage_sp 6.612295 8.422254 0.785098 0.434329 -10.1057 23.33034 -10.1057 23.33034 no_full_b: 30.33385 14.15012 2.143717 0.034582 2.246087 58.42162 2.246087 58.42162 no_half_b 11.70217 18.64852 0.627512 0.531813 -25.3148 48.71919 -25.3148 48.71919 no_rooms 11.76342 8.299796 1.417314 0.159628 -4.71155 28.23838 -4.71155 28.23838 squarefee 112.53 27.51715 4.089451 8.99E-05 57.90893 167.1512 57.90893 167.1512 a. Which variables is relevant, and which one are irrelevant b. Describe the regression via the r squared, what percent of the variation in this regression model do the variables explain