Use the following to answer the questions below:
A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on houses that had recently sold in the two towns they are considering. The variables they collected are the selling price of the home (in thousands of dollars), the size of the home (in square feet), the age of the home (in years), and the town in which the house is located (coded 1 = Canton and 0 = Potsdam). Output from their multiple regression analysis is provided.
The regression equation is
Price (in thousands) = 69.2 + 0.0627 Size (sq. ft.) - 0.632 Age + 1.6 Town
| Predictor | Coef | SE Coef | T | P |
| Constant | 69.23 | 25.10 | 2.76 | 0.008 |
| Size (sq. ft.) | 0.06267 | 0.01024 | 6.12 | 0.000 |
| Age | -0.6319 | 0.1328 | -4.76 | 0.000 |
| Town | 1.65 | 12.15 | 0.14 | 0.893 |
S = 40.0763 R-Sq = 59.3% R-Sq(adj) = 56.5%
Analysis of Variance
| Source | DF | SS | MS | F | P |
| Regression | 3 | 102936 | 34312 | 21.36 | 0.000 |
| Residual Error | 44 | 70669 | 1606 | | |
| Total | 47 | 173605 | | | |
A dotplot of the residuals and a scatterplot of the residuals versus the predicted values are provided. Discuss whether the conditions for a multiple linear regression are reasonable by referring to the appropriate plots.
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