A real estate builder wishes to determine how house size is influenced by family income, family size, and education level of the head of household. House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is measured in years. A partial computer output is shown below. SUMMARY OUTPUT Regression Statistics Multiple R 0.865 R Square 0.748 Adjusted R Square 0.726 Standard Error $5.195 Observations 50 ANOVA df SS MS F Signif F Regression 3605.7736 901.4434 0.0001 Residual 1214.2264 26.9828 Total 49 4820.0000 Coeff. St. Error t Stat P-value Intercept -1.6335 5.8078 -0.281 0.7798 Family Income 0.4485 0.1137 3.9545 0.0003 Family Size 4.2615 0.8062 5.286 0.0001 Education level -0.6517 0.4319 -1.509 0.1383Adjusted R Square 0.726 Standard Error 5.195 Observations 50 ANOVA dif SS MS Signif F Regression 3605.7736 901.4434 0.0001 Residual 1214.2264 26.9828 Total 49 4820.0000 Coeff. St. Error t Stat P-value Intercept -1.6335 5.8078 -0.281 0.7798 Family Income 0.4485 0.1137 3.9545 0.0003 Family Size 4.2615 0.8062 5.286 0.0001 Education -0.6517 0.4319 -1.509 0.1383 What fraction of the choice of house size made by a buyer is explained by their Family Income, Family Size, and Education? About 87% Not a whole lot About 75% 5.195 / 50Adjusted R Square 0.726 Standard Error 5.195 Observations 50 ANOVA df SS MS F Signif F Regression 3605.7736 901.4434 0.0001 Residual 1214.2264 26.9828 Total 49 4820.0000 Coeff. St. Error t Stat P-value Intercept -1.6335 5.8078 -0.281 0.7798 Family Income 0.4485 0.1137 3.9545 0.0003 Family Size 4.2615 0.8062 5.286 0.0001 Education -0.6517 0.4319 -1.509 0.1383 The relationship between the Independent variables and the dependent variable can be described as: O Strong Moderate O Weak PositiveA real estate builder wishes to determme bow house size is influenced by family income, family size, and education of the head of housebold. House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is measured in years. A partial computer output is shown below. SUMMARY OUTPUT Regression Statistics Multiple R 0.865 R Square 0.748 Adjusted R Square 0.726 Standard Error -5.195 Observations 50 ANOVA df SS MS F Signif F Regression 3605.7736 901.4434 0.0001 Residual 1214.2264 26.9828 Total 49 4820.0000 Coeff. St. Error Stat P-value Intercept -1.6335 5.8078 -0.281 0.7798 Family Income 0.4485 0.1137 3.9545 0.0003 Family Size 4.2615 0.8062 5.286 0.0001 Education -0.6517 0.4319 -1.509 0.1383Adjusted R Square 0.726 Standard Error 5.195 Observations 50 ANOVA df SS MS F Signif F Regression 3605.7736 901.4434 0.0001 Residual 1214.2264 26.9828 Total 49 4820.0000 Coeff. St. Error t Stat P-value Intercept -1.6335 5.8078 -0.281 0.7798 Family Income 0.4485 0.1137 3.9545 0.0003 Family Size 4.2615 0.8062 5.286 0.0001 Education level -0.6517 0.4319 -1.509 0.1383 Based on this model, do highly educated people tend to buy larger houses compared to less-educated ones? Maybe Not enough information on education O Yes O NoA real estate builder wishes to determine how house size is influenced by family income, family size, and education level of the head of household. House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is measured in years. A partial computer output is shown below. SUMMARY OUTPUT Regression Statistics Multiple R 0.865 R Square 0.748 Adjusted R Square 0.726 Standard Error 5.195 Observations 50 ANOVA df SS MS F Signif F Regression 3605.7736 901.4434 0.0001 Residual 1214.2264 26.9828 Total 49 4820.0000 Coeff. St. Error t Stat P-value Intercept -1.6335 5.8078 -0.281 0.7798 Family Income 0.4485 0.1137 3.9545 0.0003 Family Size 4.2615 0.8062 5.286 0.0001 Education -0.6517 0.4319 -1.509 0.1383