Explained Sum Of Squares
In statistics, the explained sum of squares (ESS), alternatively known as the Model Sum of Squares or Sum of Squares due to Regression, is a quantity used in describing how well a model, often a 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.
Read more about Explained Sum Of Squares: Definition, Partitioning in Simple Linear Regression, Partitioning in The General OLS Model
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