The N version of the formula is a descriptive statistic - it simply
describes the current sample (or population). The N-1 version is an
inferential statistic and takes into account degrees of freedom and the fact
that I've estimated the mean of the population.
Larry
************************************************************
Larry Z. Daily
Assistant Professor of Psychology
Department of Psychology
White Hall, Room 213
Shepherd College
Shepherdstown, West Virginia 25443
phone: (304) 876-5297
email: [EMAIL PROTECTED]
WWW: http://webpages.shepherd.edu/LDAILY/index.html
> -----Original Message-----
> From: James D. Dougan [mailto:[EMAIL PROTECTED]]
> Sent: Saturday, September 23, 2000 4:00 PM
> To: [EMAIL PROTECTED]
> Subject: Another Standard Deviation question
>
>
> All of this standard deviation talk suggests it is a good time to ask a
> question which has been bothering me for the last couple of years.....
>
> Back in the "good old days" all (or at least most) of the undergraduate
> statistics texts taught the standard deviation using ther "N-1" formula.
> The "N" formula was perhaps mentioned in a footnote, but often not
> mentioned at all...
>
> Now, virtually all of the texts teach the "N" formula in the beginning
> under descriptive stats, then introduce N-1 later under inferential.
>
> I hate the new way of doing it, partly because I have to remember new
> formulas but more because it seems to confuse the students.
>
> Why the change? What was wrong with the old method?
>
> My guess is that using the "N" formula allows one to use the z-score
> formula for Pearson r (the z-score formula for r does not work if you use
> N-1, a fact I unfortunately discovered in the middle of a lecture
> demonstration...).
>
> But - why use the z-score formula for r? The old covariance
> formula is far
> more intuitive than the z-score formula. Yes - you can easily
> show how the
> product of z-scores works the same way as covariance, but students really
> don't grasp z-scores very well to begin with and it is hard for
> them to get
> the translation back from z to covariance.
>
> My guess is that texts want to use the z-score formulation for r because
> it makes a smoother transation into multiple regression. But (sigh) I
> don't think multiple regression really belongs in a 200-level intro stat
> course....
>
> Lots of room for answers and commentaries here....shoot away....
>
> -- Jim
>
>
>
>
>
