The administrator of a small city has asked you to identify variables that influence the mean market value of houses in small midwestern cities. You have obtained data from a number of small cities,...

The administrator of a small city has asked you to identify variables that influence the mean market value of houses in small midwestern cities. You have obtained data from a number of small cities, which are stored in the data file Citydatr, with variables described in the Chapter 12 appendix. The candidate predictor variables are the median size of the house (sizehse), the property tax rate (taxrate; tax levy divided by total assessment), the total expenditures for city services (totexp), and the percent commercial property (comper).

a. Estimate the multiple regression model using all the indicated predictor variables. Select only statistically significant variables for your final equation.

b. An economist stated that since the data came from cities of different populations, your model is likely to contain heteroscedasticity. He argued that mean housing prices from larger cities would have a smaller variance because the number of houses used to compute the mean housing prices would be larger. Test for heteroscedasticity.

c. Estimate the multiple regression equation using weighted least squares with population as the weighting variable. Compare the coefficients for the weighted and unweighted multiple regression models.