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 area. They want to predict the selling price of homes (in thousands of dollars) based on the age of the home (in years). Some summary statistics, partial regression output, and a scatterplot of the relationship (with regression line) are provided.
Use two decimal places when reporting the results from any calculations, unless otherwise specified.
| Variable | Mean | StDev |
| Price (in thousands) | 140.86 | 60.78 |
| Age | 78.69 | 44.71 |
The regression equation is Price (in thousands) = 193 - 0.665 Age
Analysis of Variance
| Source | DF | SS | MS | F | P |
| Regression | 1 | 41580 | 41580 | 14.49 | 0.000 |
| Residual Error | 46 | 132025 | 2870 | | |
| Total | 47 | 173605 | | | |
Construct and interpret a 95% interval for the selling price of a single 92-year-old home.
▸ 22.77 to 240.88
We are 95% sure that selling price of a 92-year-old home is between $22,770 and $240,880.
▸ 22.77 to 240.88
We are 95% sure that the mean selling price of all 92-year-old homes is between $22,770 and $240,880.
▸ 115.57 to 148.07
We are 95% sure that selling price of a 92-year-old home is between $115,570 and $148,070.
▸ 115.57 to 148.07
We are 95% sure that the mean selling price of all 92-year-old homes is between $115,570 and $148,070.
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