Goodness-of-fit for regression

Goodness-of-fit in regression measures how well a statistical model's predicted values match the actual observed data. Think of it as assessing how accurately the model describes the real-world relationship between variables. If the model fits well, the predicted points are close to the actual data points, indicating reliable predictions. Metrics like R-squared quantify this fit; a higher value suggests the model explains more of the data's variation, while a lower value indicates it might not be capturing the relationship effectively. Overall, goodness-of-fit helps us evaluate the usefulness of the regression model for understanding and predicting data.