Residuals

Residuals refer to the differences between observed values and the values predicted by a model. In simpler terms, when we make predictions using a statistical model, residuals show how accurate those predictions are. If we predict someone’s height based on certain factors, the residual would be the difference between the predicted height and the actual height. Smaller residuals indicate a better fit of the model to the data, while larger residuals suggest the model may not be capturing the relationship well. Analyzing residuals helps improve models and understand their effectiveness.