My son and I have written a statistics tutorial for the computer and in
it we provide an answer to your question. The tutorial is available for
$19.95 from my son's websit:
www.animatedsoftware.com
but if you send me an email I can arange for you to download a review
copy free.
Howard > Hoffman
steinberg wrote:
> I am seeking better understanding of the concept of degrees of
> freedom. Here's what I think I know:
>
> 1) Whenever a sum of squares is estimated, the result is
> constrained by the fact that the deviations about the mean must
> sum to zero. The number of scores free to vary is therefor n-1.
>
> 2) When estimating the population SD from a sample, SS/n is a
> biased estimate because the sample tends to be less variable than
> the population from which it comes. SS/(n-1) is an unbiased
> estimate.
>
> Here are the problems I am having:
>
> a) I have difficulty seeing the relation between 1 and 2 above.
> That is, given that 1 is true, it does not seem to imply that n-1
> is better than n when estimating sigma. This is implied from 2.
>
> b) I am looking at the ANOVA table for a regression with two
> preditors and n=395. The total df is 394. I can explain that from
> either 1 or 2 above. However the df for regression is 2. Doesn't
> the fact that a sum of squares was computed for regression have
> an impact here as in 1 above? Isn't SSR also an estimate as in 2
> above?
>
> Milton Steinberg
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