Extracted text: The slope coefficient for Bedroom indicates that, holding other explanatory variables constant, Multiple Choice for each additional bedroom the rent is predicted to increase by $0.40 for each additional bedroom the rent is predicted to increase by $218 for each additional bedroom the rent is predicted to increase by $280 for each additional bedroom the rent is predicted to increase by $95
Extracted text: A real estate analyst believes that the three main factors that influence an apartment's rent in a college town are the number of bedrooms, the number of bathrooms, and the apartment's square footage. For 40 apartments, she collects data on the rent (y, in $), the number of bedrooms (x1), the number of bathrooms (x2), and its square footage (x3). She estimates the following model as Rent = Bo + ß1 Bedroom + B2 Bath + B3 Sqft + ɛ. The following ANOVA table shows a portion of the regression results. df MS Regression 3 5,694,798 1,898,266 50.88 Residual 36 1,343,142 37,310 Total 39 7,037,940 Coefficients Standard Error t-stat p-value Intercept 280 106.0 2.64 0.0030 Bedroom 218 57.5 3.79 0.0005 Bath 95 53.8 1.77 0.1172 Sqft 0.4 0.1 4 0.0284 The slope coefficient for Bedroom indicates that, holding other explanatory variables constant, Multiple Choice for each additional bedroom the rent is predicted to increase by $0.40 for each additional bedroom the rent is predicted to increase by $218