In a scatterplot with a line of best fit, if the line's predicted y-value is higher than the actual y-value for a data point, what does this indicate?

In a scatterplot with a line of best fit, if the line's predicted y-value is higher than the actual y-value for a data point, what does this indicate?

• A. The line overestimates that data point
• B. The line underestimates that data point
• C. The data point lies on the line
• D. The line has zero slope

Answer: (B)

The line of best fit gives predicted y-values for each x, and the difference between the actual y and that prediction shows how far off the line is. If the line’s predicted y is higher than the actual y, the line is predicting too large a value for that x, so it overestimates that data point. The data point would sit below the line at that x, and the residual (actual minus predicted) is negative. If the predicted y were lower than the actual, the line would underestimate the point (positive residual). A point lies on the line only when the actual and predicted values match exactly, and a line with zero slope would predict the same y for all x, which isn’t about this specific mismatch.

The line of best fit gives predicted y-values for each x, and the difference between the actual y and that prediction shows how far off the line is. If the line’s predicted y is higher than the actual y, the line is predicting too large a value for that x, so it overestimates that data point. The data point would sit below the line at that x, and the residual (actual minus predicted) is negative. If the predicted y were lower than the actual, the line would underestimate the point (positive residual). A point lies on the line only when the actual and predicted values match exactly, and a line with zero slope would predict the same y for all x, which isn’t about this specific mismatch.