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# error sum of squares

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• Sum of squares — is a concept that permeates much of inferential statistics and descriptive statistics. More properly, it is the sum of the squared deviations . Mathematically, it is an unscaled, or unadjusted measure of dispersion (also called variability). When …   Wikipedia

• Explained sum of squares — In statistics, an explained sum of squares (ESS) is the sum of squared predicted values in a standard regression model (for example y {i}=a+bx {i}+epsilon {i}), where y {i} is the response variable, x {i} is the explanatory variable, a and b are… …   Wikipedia

• Residual sum of squares — In statistics, the residual sum of squares (RSS) is the sum of squares of residuals. It is the discrepancy between the data and our estimation model. The smaller this discrepancy is, the better the estimation will be.:RSS = sum {i=1}^n (y i f(x… …   Wikipedia

• 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 in an analysis of variance, used in the numerator in an F test of the null hypothesis… …   Wikipedia

• Residual Sum Of Squares - RSS — A statistical technique used to measure the amount of variance in a data set that is not explained by the regression model. The residual sum of squares is a measure of the amount of error remaining between the regression function and the data set …   Investment dictionary

• Ordinary least squares — This article is about the statistical properties of unweighted linear regression analysis. For more general regression analysis, see regression analysis. For linear regression on a single variable, see simple linear regression. For the… …   Wikipedia

• Linear least squares/Proposed — Linear least squares is an important computational problem, that arises primarily in applications when it is desired to fit a linear mathematical model to observations obtained from experiments. Mathematically, it can be stated as the problem of… …   Wikipedia

• Least squares — The method of least squares is a standard approach to the approximate solution of overdetermined systems, i.e., sets of equations in which there are more equations than unknowns. Least squares means that the overall solution minimizes the sum of… …   Wikipedia

• Linear least squares (mathematics) — This article is about the mathematics that underlie curve fitting using linear least squares. For statistical regression analysis using least squares, see linear regression. For linear regression on a single variable, see simple linear regression …   Wikipedia

• Linear least squares — is an important computational problem, that arises primarily in applications when it is desired to fit a linear mathematical model to measurements obtained from experiments. The goals of linear least squares are to extract predictions from the… …   Wikipedia

• Non-linear least squares — is the form of least squares analysis which is used to fit a set of m observations with a model that is non linear in n unknown parameters (m > n). It is used in some forms of non linear regression. The basis of the method is to… …   Wikipedia