6. Remember that the least-squares line may be the “best” line (in that it has a smaller sum of squared deviations than any other line), but that doesn’t necessarily mean that the line will produce good predictions. Be cautious of predictions based on a least-squares line without any information about the adequacy of the linear model, such as se and r2.