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 | | | |
What is the estimated slope in this regression model? Interpret the slope in context.
▸ -0.665
For each additional year of age, the selling price of homes in this portion of northern New York is predicted to increase by $665.
▸ 193
For each additional year of age, the selling price of homes in this portion of northern New York is predicted to decrease by $193.
▸ 193
For each additional year of age, the selling price of homes in this portion of northern New York is predicted to increase by $193.
▸ -0.665
For each additional year of age, the selling price of homes in this portion of northern New York is predicted to decrease by $665.
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