# Quant-Regression

Is this understanding correct?

**Regression** SS is the sum of squares that is explained by your model. **Residual **SS is the sum of squares that is not explained by your model.

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The regression sum of squares is the

portion of the variance of the dependent variablethatexplained by the regression. The residual sum of squares is theisportion of the variance of the dependent variablethatexplained by the regression.is notSimplify the complicated side; don't complify the simplicated side.

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And when we say that the expected value of the error term is zero, we are saying that the mean should be zero and not the absolute value, right? Or is it that even the absolute value of the error term should be zero, because then, actual will be equal to predicted.

Yes, the mean is zero.

Simplify the complicated side; don't complify the simplicated side.

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Not the absolute value of the error term, is it? Sorry to be bothering you again.

If the absolute value of the error term is zero, then the error term is zero, so there is no deviation from the regression line.

Some errors are positive; others are negative. The mean is zero.

Simplify the complicated side; don't complify the simplicated side.

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