the residual sum of squares (RSS), also known as the sum of squared residuals (SSR) or the sum of squared estimate of errors (SSE), is the sum of the...

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...

plus the residual sum of squares. For proof of this in the multivariate OLS case, see partitioning in the general OLS model. In analysis of variance (ANOVA)...

calculating variance Errors and residuals Least squares Mean squared error Residual sum of squares Root-mean-square deviation Variance decomposition...

Least squares For the "sum of squared differences", see Mean squared error For the "sum of squared error", see Residual sum of squares For the "sum of squares...

method of least squares is a parameter estimation method in regression analysis based on minimizing the sum of the squares of the residuals (a residual being...

squared lengths. In the example above, the residual sum-of-squares is ∑ i = 1 n ( X i − X ¯ ) 2 = ‖ X 1 − X ¯ ⋮ X n − X ¯ ‖ 2 . {\displaystyle \sum...

lack-of-fit sum of squares to differ from the sum of squares of residuals, there must be more than one value of the response variable for at least one of the...

In statistics, ordinary least squares (OLS) is a type of linear least squares method for choosing the unknown parameters in a linear regression model...

partition of sums of squares is a concept that permeates much of inferential statistics and descriptive statistics. More properly, it is the partitioning of sums...