A residual plot shows the difference between the measured values and the predicted values against the true values.
The residual plot shows disagreement between the data and the fitted model. The ideal residual plot (called the null residual plot) shows a random scatter of points forming an approximately constant width band around the identity line.
It is important to check the fit of the model and the assumptions:
||How to check
|Model function is linear
||The points will form a pattern when the model function is not linear.
||If the points tend to form an increasing, decreasing, or non-constant width band, the variance is not constant and you should consider using weighted regression.
||A histogram of the residuals should form a normal distribution. This is an assumption of linear regression. Deming regression with Jacknife standard errors is robust to this assumption. Passing-Bablok regression is non-parametric and this assumption does not apply.