The data below were collected from a sample of 15 houses to develop a model for predicting assessed
Question: The data below were collected from a sample of 15 houses to develop a model for predicting assessed value (in $1000) based on the heating area (in thousands of square feet) and whether or not the house has a fire-place.
Value | Heating | Fireplace |
84.4 | 2 | Yes |
77.4 | 1.71 | No |
75.7 | 1.45 | No |
85.9 | 1.76 | Yes |
79.1 | 1.93 | No |
70.4 | 1.2 | Yes |
75.8 | 1.55 | Yes |
85.9 | 1.93 | Yes |
78.5 | 1.59 | Yes |
79.2 | 1.5 | Yes |
86.7 | 1.9 | Yes |
79.3 | 1.39 | Yes |
74.5 | 1.54 | No |
83.8 | 1.89 | Yes |
76.8 | 1.59 | No |
a. Fit a first-order model for y = assessed value, using heating area and fire-place availability as independent variables. Along with your other residual plots and scatter plots, plot a partial residual plot for Heating. You will have to create the partial residual plot (maybe in Excel), since Minitab does not do this.
b. Next, fit a model with an interaction term. Comment on the results. Use a test for nested models to verify your conclusion.
c. Finally, fit a model with the two first-order terms as well as Heating^2 (but no interaction term). Perform a test for nested models to determine whether this model is superior to the first-order model.
Deliverable: Word Document
