A real estate analyst believes that the three main factors that influence an apartment’s rent in a college

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?

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