Changing standard error to standard deviation.

AI Thread Summary
To convert standard error to standard deviation, the correct formula is STD ERROR = STD DEV / (n^0.5), where n represents the sample size. The discussion clarifies that degrees of freedom, defined as N minus the number of X coefficients, is not necessary for this conversion. Additionally, the formula for standard deviation is mentioned as STD DEV = SUM OF SQUARES / ((n-1)^0.5). There is caution against using "degrees of freedom" in this context, as it applies specifically to statistical tests and differs from sample size. Understanding these distinctions is crucial for accurate statistical analysis.
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Hi all,

I've done a regression and have the Standard Error of the X co-efficient (i.e. the slope).

How do I change this figure to the standard deviation?

Is the formula

STD DEV = (STD ERROR)/(degrees of freedom)^0.5

Where degrees of freedom = N - number of X coefficients.

?

Thanks.
 
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Actually, I believe the formula is STD ERROR = STD DEV / (n^0.5)

Moreover:

STD DEV = SUM OF SQUARES / ((n-1)^0.5)

I'm reluctant to use the term "degrees of freedom" because this measure doesn't come into play unless a statistical test is involved, and is not the same as the sample size, "n."
 
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