1. Residuals

2. Residual or Deviation A residual or deviation = y data – y line = y actual – y theoetical = y experiment - y model A residual plot is if for each data point, you keep the x and make the y-value equal to the residual (AKA deviation) There should be no obvious pattern to the deviation plot If there is an obvious pattern then the model is probably inadequate and you need to switch to a parabola, square root, etc.

3. Residual or Deviation A residual or deviation = y data – y line The data point at x = 8 is 0.34 units below the line, so the residual plot has the point (8, –0.34). The data point at x = 2 is 0.88 units above the line so the residual plot has the point (2, 0.88) Normal PlotResidual Plot

4. Residual Plot More scatter at higher x-values, so there’s more predictability at low number of slices.

5. Residual Plot This looks linear, but the residual shows hidden curvature. Actual equation y = 0.01x 2 + 2.2x + 1 Subtle curvature is often revealed in residual plot