Refer to the CDI data set in Appendix C.2.
a. For each geographic region, regress the number of serious crimes in a CDI (Y) against population density (X1, total population divided by land area), per capita personal income (X2), and percent high school graduates (X3). Use first-order regression model (6.5) with three predictor variables. State the estimated regression functions.
b. Are the estimated regression functions similar for the four regions? Discuss.
c. Calculate MSE and R2 for each region. Are these measures similar for the four regions? Discuss.
d. Obtain the residuals for each fitted model and prepare a box plot of the residuals for each fitted mode L Interpret your plots and state your findings.
The city tax assessor was interested in predicting residential home sales prices in a midwestern
city as a function of various characteristics of the home and surrounding property. Data on 522 arms-length transactions were obtained for home sales during the year 2002. Each line of the data set has an identification number and provides information on 12 other variables. The 13 variables are: