Explained Sum of Squares (ESS) Measure
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An Explained Sum of Squares (ESS) Measure is a sum of squares that ...
- Context:
- It can be a component of a Total Sum of Squares (TSS) Measure.
- …
- Counter-Example(s):
- See: Explained Variance Regression Score, Regression Analysis.
References
2017
- (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/Explained_sum_of_squares Retrieved:2017-10-2.
- 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 the residual sum of squares RSS), 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.