Changing standard error to standard deviation.

In summary, The speaker has performed a regression and has the Standard Error of the X co-efficient. They are asking how to convert this figure to the standard deviation and provide a possible formula for doing so. Another speaker suggests a different formula using the sample size rather than the degrees of freedom. The original speaker expresses hesitation about using the term "degrees of freedom."
  • #1
operationsres
103
0
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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  • #2
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."
 

What is the difference between standard error and standard deviation?

Standard error measures the variability of a sample mean from the true population mean, while standard deviation measures the variability of individual data points from the mean.

Why is it important to convert standard error to standard deviation?

Converting standard error to standard deviation allows for a better understanding of the spread of the data and the accuracy of the sample mean. It also allows for comparison between different samples with different sample sizes.

How do you convert standard error to standard deviation?

To convert standard error to standard deviation, multiply the standard error by the square root of the sample size. This is because the standard deviation is the square root of the variance, and the variance is equal to the standard error squared.

What does the value of standard error tell us about the sample?

The smaller the standard error, the more precise the estimate of the sample mean is to the true population mean. A larger standard error indicates a larger variability in the sample and a less accurate estimate of the population mean.

Can standard error be larger than standard deviation?

No, standard error is always smaller than standard deviation. This is because standard deviation measures the spread of individual data points, while standard error measures the spread of the sample mean.

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