Residual

A residual is the gap between an actual observed value and the value the regression line predicted for it: residual = actual − predicted. A positive residual means the real point sits above the line (the model under-predicted); a negative one means it sits below.

Residuals are how you check whether a model is trustworthy, not just whether it fits. After fitting, you plot the residuals: if they scatter randomly around zero with no pattern, the straight-line assumption looks fine; if they form a curve, a funnel shape, or drift, the model is missing something and your predictions and uncertainty estimates may be misleading.