TABLE 12-4 A real estate builder wishes to determine how house size (House) is influenced by family income (Income), family size (Size), and education of the head of household (School) . House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is in years. The builder randomly selected 50 families and ran the multiple regression. Microsoft Excel output is provided 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 StdError t Stat P-value Intercept -1. 6335 5. 8078 -0 . 281 0. 7798 Income 0. 4485 0. 1137 3.9545 0 . 0003 Size 4. 2615 0 . 8062 5. 286 0. 0001 School -0.6517 0 . 4319 -1. 509 0. 1383 17. Referring to Table 12-4, which of the following values for the level of significance is the smallest for which the regression model as a whole is significant? a. 0. 00005 b. 0.001 C. 0.01 d. 0.05 18. Referring to Table 12-4, one individual in the sample had an annual income of $100,000, a family size of 10, and an education of 16 years. This individual owned a home with an area of 7,000 square feet (House = 70.00) . What is the residual (in hundreds of square feet) for this data point? a. 7.40 b. 2.52 C. -2.52 d. -5. 40