7. A dataset contains information about a random sample of 200 house sales in a town in the Pacific Northwest. A regression model was fit for predicting the selling price of a house (in thousands of dollars) using house size (sq ft) and whether the house has a garage as predictors. The ANOVA table is given below: F p value DF Sum of Square's 40 0001 Source 1 390.588 215 26 0.0030 House Size 58 076 9.06 Garage Error 197 1263472 Total 2.668 870 Does SSHouseSize + SSGarage = SSModel? A. No, because there is likely covariation between size and garage in this observational study B. No, because there is no covariation among explanatory variables when the data come form a random sample C. Yes, because there is likely covariation between size and garage in this observational study D. Yes, because there is no covariation among explanatory variables when the data come from a random sample 8. A dataset contains information about a random sample of 200 house sales in a town in the Pacific Northwest. A regression model was fit for predicting the selling price of a house (in thousands of dollars) using house size (sq ft), garage (garage = 1 if the house has a garage and 0 otherwise), and the interaction between size and garage. Term SE Intercops restat 141 835 18 130 pavalue Size 7.82 0.039 40 0001 0 006 7 07 Quran ind 0 0001 -120.392 24. 163 Size x Garage_ind 4.98 0.062