Final answer:
If the unknown falls below the linear range, it means the data point is not within the range of the line of best fit. Treat it as a potential outlier and analyze it separately.
Step-by-step explanation:
If the unknown falls below the linear range, it means that the data point is not within the range of values that the line of best fit was derived from. In this case, it is not appropriate to use the line of best fit to make predictions or draw conclusions about the data. Instead, you should consider the point a potential outlier and analyze it separately.
In graphing calculators like the TI-83, 83+, or 84+, you can visually identify outliers by measuring the vertical distance from any data point to the corresponding point on the line of best fit.
If that distance is equal to 2s or more (where s represents the standard deviation), then the data point can be considered too far from the line of best fit and treated as an outlier.
By identifying and analyzing outliers separately, you can ensure that your conclusions and predictions are based on reliable data and within the appropriate range of values.