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The image shows a problem regarding the association between weekly income and weekly grocery expenditures. A scatterplot with a least-squares regression line is provided, and you are asked to estimate the residual (or error) for a family that has a weekly income of $805.

### Steps to solve:

1. **Find the predicted grocery bill** for a family with an income of $805 using the least-squares regression line in the scatterplot.
   - From the graph, visually trace the $805 income point on the horizontal axis, and follow it up to the regression line. 
   - Estimate the corresponding value for the grocery bill on the vertical axis.

2. **Calculate the residual (error):**
   \[
   \text{Residual} = \text{Actual Value} - \text{Predicted Value}
   \]
   The "actual value" is unknown in this case, but since you are asked to estimate the error, you can use the general method above to predict the grocery bill from the line and assess the difference between the predicted and actual points on the graph.

Would you like me to try estimating the predicted value and residual for the $805 income directly from the graph?

An economist conducted a study of the possible association between weekly income and weekly grocery expenditures. One family reported a weekly income of $805. Estimate the residual (error) in their predicted grocery bill.

Learn how to estimate residuals from a least-squares regression line using a real-world example of weekly income and grocery expenditures. This problem covers key statistical concepts, including linear regression and residual calculation. Suitable for high school students in Grades 10-12.

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