# Residual sum of squares

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In statistics, the residual sum of squares (RSS) is the sum of squares of residuals.

In a standard regression model $y_i = a+bx_i+\varepsilon_i\,$, where a and b are coefficients, y and x are the regressand and the regressor, respectively, and ε is the error term. The sum of squares of residuals is the sum of squares of estimates of εi.

In general: total sum of squares = explained sum of squares + residual sum of squares.