Revision as of 01:00, 19 April 2019 edit 128.135.98.52 (talk) →‎Partitioning in the general ordinary least squares model ← Previous edit		Revision as of 09:48, 13 November 2019 edit undo 129.240.43.144 (talk) →‎Definition: deleted redundant (and possibly confusing) descriptive text Next edit →
Line 13: :<math>\hat{y}_i=\hat{a}+\hat{b}_1 x_{1i} + \hat{b}_2 x_{2i} + \cdots \, </math> is the ''i''<sup> th</sup> predicted value of the response variable. The ESS is ~~the sum of the squares of the differences of the predicted values and the mean value of the response variable~~then: :<math>\text{ESS} = \sum_{i=1}^n \left(\hat{y}_i - \bar{y}\right)^2.</math>

Explained sum of squares: Difference between revisions