Residual Sum of Squares

Residual Sum of Squares (RSS) is a measure used in statistical modeling to assess how well a model fits data. It calculates the total squared differences between the observed values and the values predicted by the model. Smaller RSS indicates the model's predictions closely match actual data, showing a better fit, while larger RSS suggests the model is less accurate. In essence, RSS sums up the errors, emphasizing larger deviations more due to squaring, helping us evaluate and compare different models or improvements.