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Total sum of squares

Index Total sum of squares

In 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. [1]

16 relations: Academic Press, Analysis of variance, Explained sum of squares, Kantilal Mardia, Lack-of-fit sum of squares, Linear discriminant analysis, Linear model, Matrix (mathematics), Mean, Multivariate analysis of variance, Partition of sums of squares, Regression analysis, Residual sum of squares, Square (algebra), Statistics, Summation.

Academic Press

Academic Press is an academic book publisher.

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Analysis of variance

Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among group means in a sample.

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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 ("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.

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Kantilal Mardia

Kantilal Vardichand ("Kanti") Mardia (born 1935) is a statistician specializing in directional statistics, multivariate analysis, geostatistics, statistical bioinformatics and statistical shape analysis.

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Lack-of-fit sum of squares

In statistics, a sum of squares due to lack of fit, or more tersely a lack-of-fit sum of squares, is one of the components of a partition of the sum of squares of residuals in an analysis of variance, used in the numerator in an F-test of the null hypothesis that says that a proposed model fits well.

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Linear discriminant analysis

Linear discriminant analysis (LDA), normal discriminant analysis (NDA), or discriminant function analysis is a generalization of Fisher's linear discriminant, a method used in statistics, pattern recognition and machine learning to find a linear combination of features that characterizes or separates two or more classes of objects or events.

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Linear model

In statistics, the term linear model is used in different ways according to the context.

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Matrix (mathematics)

In mathematics, a matrix (plural: matrices) is a rectangular array of numbers, symbols, or expressions, arranged in rows and columns.

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Mean

In mathematics, mean has several different definitions depending on the context.

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Multivariate analysis of variance

In statistics, multivariate analysis of variance (MANOVA) is a procedure for comparing multivariate sample means.

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Partition of sums of squares

The partition of sums of squares is a concept that permeates much of inferential statistics and descriptive statistics.

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Regression analysis

In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships among variables.

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Residual sum of squares

In statistics, the residual sum of squares (RSS), also known as the sum of squared residuals (SSR) or the sum of squared errors of prediction (SSE), is the sum of the squares of residuals (deviations predicted from actual empirical values of data).

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Square (algebra)

In mathematics, a square is the result of multiplying a number by itself.

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Statistics

Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.

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Summation

In mathematics, summation (capital Greek sigma symbol: ∑) is the addition of a sequence of numbers; the result is their sum or total.

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References

[1] https://en.wikipedia.org/wiki/Total_sum_of_squares

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