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In [[statistics|statistical data analysis]] the '''total sum of squares''' (TSS or SST) is a quantity that appears as part of a standard way of presenting results of such analyses. It is defined as being the sum, over all observations, of the squared differences of each observation from the overall [[mean]].<ref>Everitt, B.S. (2002) ''The Cambridge Dictionary of Statistics'', CUP, ISBN 0-521-81099-X</ref>
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In [[statistics|statistical]] [[linear model]]s, (particularly in standard [[regression model]]s), the '''TSS''' is the [[sum]] of the [[square (algebra)|square]]s of the difference of the dependent variable and its [[mean]]:
 
:<math>\sum_{i=1}^{n}\left(y_{i}-\bar{y}\right)^2</math>
 
where <math>\bar{y}</math> is the mean.
 
For wide classes of linear models, the total sum of squares equals the [[explained sum of squares]] plus the [[residual sum of squares]]. For a proof of this in the multivariate OLS case, see [[Explained sum of squares#Partitioning in the general OLS model|partitioning in the general OLS model]].
 
In [[analysis of variance]] (ANOVA) the total sum of squares is the sum of the so-called "within-samples" sum of squares and "between-samples" sum of squares, i.e., partitioning of the sum of squares.
In [[multivariate analysis of variance]] (MANOVA) the following equation applies<ref name="MardiaK1979Multivariate">{{Cite book
| author = [[K. V. Mardia]], J. T. Kent and J. M. Bibby
| title = Multivariate Analysis
| publisher = [[Academic Press]]
| year = 1979
| isbn = 0-12-471252-5
}} Especially chapters 11 and 12.</ref>
:<math>\mathbf{T} = \mathbf{W} + \mathbf{B},</math>
where '''T''' is the total sum of squares and products (SSP) [[Matrix (mathematics)|matrix]], '''W''' is the within-samples SSP matrix and '''B''' is the between-samples SSP matrix.
Similar terminology may also be used in [[linear discriminant analysis]], where '''W''' and '''B''' are respectively referred to as the within-groups and between-groups SSP matrics.<ref name="MardiaK1979Multivariate"/>
 
==See also==
*[[Sum of squares (statistics)]]
*[[Lack-of-fit sum of squares]]
 
==References==
{{Reflist}}
 
[[Category:Regression analysis]]
[[Category:Least squares]]

Latest revision as of 14:39, 12 January 2015

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