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After computing the standard error of regression, my answer is 3.55 what does the value mean

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  • $\begingroup$ It depends on which quantity you're calling "the standard error of regression". $\endgroup$
    – Glen_b
    Oct 2, 2014 at 3:13
  • $\begingroup$ @ Glen: here is how I defined the standard error of the model Se = √ Σ(Yi – Yhat)2 / n-2 $\endgroup$
    – Anie
    Oct 2, 2014 at 3:20

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Assuming by standard error of regression you mean the residual standard deviation, $s$, where $s^2=\frac{\text{RSS}}{n-p}$ -- e.g. like this (edited regression output from R):

enter image description here

then that quantity, often called $s$, represents an estimate of the standard deviation of the error term in your regression model, a typical distance of points from the regression line.

It's measured in the units of the original observations.

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  • $\begingroup$ Thanks a bunch Glen_b. It follows then from my computed value that the typical distance of points from the regression line for my data is 3.55. Sorry I really don't understand the last part - "measured in units of the original observation". My sample population is 12 with degree of freedom = 10.Thanks so far for your assistance just a bit confused cos different write ups have different explanations $\endgroup$
    – Anie
    Oct 2, 2014 at 3:35
  • $\begingroup$ What I meant is that if your response is measured in hours or meters or units of IQ, then so is $s$. If you write a new question outlining what contradictions you see in the writeups (preferably with quotes), you might be able to get those particular issues clarified. $\endgroup$
    – Glen_b
    Oct 2, 2014 at 4:26
  • $\begingroup$ @Glen_b : how we can interpret residual standard deviation? does Residual SD helps in drawing any inference from regression output? $\endgroup$
    – user269867
    Oct 6, 2014 at 12:51
  • $\begingroup$ Besides the interpretation I mentioned in my answer, it's used in finding every parameter standard error, and in the F-statistic. $\endgroup$
    – Glen_b
    Oct 6, 2014 at 12:54

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