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Concept explainers
Home Sale Prices. Refer to Example B.18 on page B-67, regarding the relationship between the sale price of a home and its size in square feet. In that example, we used the presence/absence of a swimming pool as a qualitative predictor variable. Here we consider using the type of roof on the home as a predictor variable. The homes in this data set have either a tile roof or a non-tile roof. The data for the 88 homes are in the table on page B-89.
We introduced the indicator variable roof defined by
Roof =
- a. Output B.52 on page B-90 shows a plot of price versus size, with the plot symbol being a solid black circle for homes having a non-tile roof. Based on this plot does it appear that roof is a useful predictor variable? Explain your answer.
- b. We obtained the
regression analysis of price on size and roof shown in Output B.53 on page B-90. Conduct the t-tests for the individual utility of the two predictor variables at the 5% level of significance. Interpret your results. - c. Based on Output B.53, obtain the individual regression equations relating price to size for homes having tile roofs and for homes having non-tile roofs.
- d. Outputs B.54(a)–(d) on page B-91 provide plots of residuals versus fitted values, residuals versus size, residuals versus roof, and a normal probability plot of residuals, respectively. Perform a residual analysis to assess the appropriateness of the regression equation, constancy of the conditional standard deviations, and normality of the conditional distributions. Check for outliers and influential observations.
- e. Output B.55 on page B-91 provides a plot of price versus size with the regression lines for homes with tile roofs and with non-tile roofs. Based on this output and your residual analysis in part (d), do you feel that this model fits the data well? Explain your answer.
- f. To check for possible interaction between the two predictor variables, we obtained the regression analysis of price on size, roof and roof size. The output is in Output B.56 on page B-92. Is there an interaction between size and roof that is, is the cross-product term roof-size a useful predictor variable in the regression equation that also contains size and roof? Use α = 0.05.
Regression Analysis: PRICE versus SIXE, ROOF
OUTPUT B.53
Regression output for Exercise B.67
OUTPUT B.56 Regression output for Exercise B.67
Regression Analysis: PRICE versus SIZE, ROOF, ROOF*SIZE
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Chapter B Solutions
Introductory Statistics (10th Edition)
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