b) the data is not good for because r=.67 c) not a good fit because s = 59.83 d) approximately 66% of the change in price of a house xan be explained by the 3 independent variables

Answer: The hypothesis is a one tail test. Question 6 Linear Regression: X Consider the following data for a multiple regression model relating housing prices (in thousands of dollars) to the number of bedrooms in the house, the size of the lot and the size of the house in square feet. Summary Output Regression Statistics Multiple R 0.82 R Square 0.67 Adjusted R Square 0.66 Standard Error 59.83 Observations 88 ANOVA SS MS F Significance F Regression 3 617130.7 205710 57.46 2.6696 Residual 84 300723 3580.05 Total 87 917854.5 Standard Coefficents error t-test P-value Lower 956 Uppi Intercept -21.77 29.48 -0.7386 0.46 -80.38 Bedrooms 13.85 9.01 1.54 0.13 -4.065 Lot size 0.002 0.00064 3.22 0.002 0.00079 0. Square feet 0.1228 0.013 9.275 1.65E-14 0.09645 Which statement below best describes the goodness-of-fit? Selected Answer: The data is a good fit because the F- value is 57.46