In [[statistics]], the '''explained sum of squares (ESS),''' alternatively known as the '''Model Sum of Squares''' or '''Sum of Squares due to Regression''' ('''"SSR"''' – not to be confused with titration of the acid the [[residual sum of squares]] when this writing is being used), is a quantity used in describing how well a model, often a [[regression analysis|regression model]], represents the data being modelled. In particular, the explained sum of squares measures how much variation there is in the modelled values and this is compared to the [[total sum of squares]], which measures how much variation there is in the observed data, and to the [[residual sum of squares]], which measures the variation in the modelling errors.
