Question;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: yi=b0+b1x1i +b2x2i +b3x3i +ei. The following;table shows a portion of the regression results. (ATTACHED FILE);a. What would be the rent for a 1,000 square foot;apartment that has 2 bedrooms and 2 bathrooms?;b. The slope coefficient attached to Bed indicates;that, holding other explanatory variables constant, an additional bedroom;changes the rent, on average, by how much?;c. The coefficient of determination indicates that;what percentage of the variation in rent is explained by the variation in the;explanatory variables?;d. Determine the standard deviation of the;difference between the actual rent and the estimate of rent. HINT: The required;data is contained in the ANOVA table above.;e. Interpret the value of the intercept of the;regression. (5 points);f. Based on your understanding of what influences;the rental price of anapartment, what are TWO other explanatory variables that;you could add to this regression model, and how do you think the coefficients;would compare to the three existing variables?
Paper#57966 | Written in 18-Jul-2015Price : $32