Data Science Numerical Analysis
Residuals are the differences between the observed values and the predicted values obtained from a statistical model. They provide insight into how well a model fits the data; smaller residuals indicate a better fit, while larger residuals suggest potential issues with the model's accuracy. Analyzing residuals helps identify patterns or anomalies that could affect the validity of the model used in least squares approximation.
congrats on reading the definition of Residuals. now let's actually learn it.