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:
| Assumption | How to check |
|---|---|
| Model function is linear | The points will form a pattern when the model function is not linear. |
| Constant variance | 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. |
| Normality | 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. |
From the Statistical Reference Guide for Analyse-it 6.24.0: https://analyse-it.com/docs/user-guide/method-comparison/residual-plot
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