Residual Sum of Squares
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High Quality Content by WIKIPEDIA articles! In statistics, the residual sum of squares (RSS) is the sum of squares of residuals. It is a measure of the discrepancy between the data and an estimation model. A small RSS indicates a tight fit of the model to the data. 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 ? is the "error term." The sum of squares of residuals is the sum of squares of estimates of ?i.

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High Quality Content by WIKIPEDIA articles! In statistics, the residual sum of squares (RSS) is the sum of squares of residuals. It is a measure of the discrepancy between the data and an estimation model. A small RSS indicates a tight fit of the model to the data. 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 ? is the "error term." The sum of squares of residuals is the sum of squares of estimates of ?i.