On Thu, Feb 4, 2010 at 11:07 AM, Peng Yu <pengyu...@gmail.com> wrote:
> I'm so surprised that even this basic definition does not have unique > name in the nomenclature, which might cause confusion in certain > context. Just some of my thought---if both definitions are OK, then > the wiki page might be revised > http://en.wikipedia.org/wiki/Variance#Population_variance_and_sample_variance. > After all, many none pure statisticians relies on wiki for easy access > of some simple terms. I believe the nomenclature in your link is pretty well accepted. The point made earlier is that when sampling one uses (n-1) to get an unbiased estimate of the *population* value, so one needs to be careful w/ semantics and it's really better to be mathematically explicit. Also when we discuss the variance of a random variable we are referring to its 2nd central moment (Var X = E(X - E X)^2), so again the definition is context dependent. Kingsford > > >>> -----Original Message----- >>> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r- >>> project.org] On Behalf Of Ista Zahn >>> Sent: Tuesday, February 02, 2010 12:03 PM >>> To: Peng Yu >>> Cc: r-h...@stat.math.ethz.ch >>> Subject: Re: [R] population variance and sample variance >>> >>> Probably a simple typo, but just to keep things straight: you want to >>> divide by n when describing the standard deviation of a sample, and >>> divide by n-1 when estimating a population standard deviation (your >>> initial description had it backwards I think). >>> >>> On Tue, Feb 2, 2010 at 5:25 PM, Peng Yu <pengyu...@gmail.com> wrote: >>> > On Mon, Oct 19, 2009 at 12:53 PM, Kingsford Jones >>> > <kingsfordjo...@gmail.com> wrote: >>> >>> sum((x-mean(x))^2)/(n) >>> >> [1] 0.4894708 >>> >>> ((n-1)/n) * var(x) >>> >> [1] 0.4894708 >>> > >>> > But this is not a built-in function in R to do so, right? >>> > >>> >> hth, >>> >> Kingsford >>> >> >>> >> On Mon, Oct 19, 2009 at 9:30 AM, Peng Yu <pengyu...@gmail.com> >>> wrote: >>> >>> It seems that var() computes sample variance. It is straight >>> forward >>> >>> to compute population variance from sample variance. However, I >>> feel >>> >>> that it is still convenient to have a function that can compute >>> >>> population variance. Is there a population variance function >>> available >>> >>> in R? >>> >>> >>> >>> $ Rscript var.R >>> >>>> set.seed(0) >>> >>>> n = 4 >>> >>>> x = rnorm(n) >>> >>>> var(x) >>> >>> [1] 0.6526278 >>> >>>> sum((x-mean(x))^2)/(n-1) >>> >>> [1] 0.6526278 >>> >>>> >>> >>> >>> >>> ______________________________________________ >>> >>> R-help@r-project.org mailing list >>> >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> >>> PLEASE do read the posting guide http://www.R-project.org/posting- >>> guide.html >>> >>> and provide commented, minimal, self-contained, reproducible code. >>> >>> >>> >> >>> > >>> > ______________________________________________ >>> > R-help@r-project.org mailing list >>> > https://stat.ethz.ch/mailman/listinfo/r-help >>> > PLEASE do read the posting guide http://www.R-project.org/posting- >>> guide.html >>> > and provide commented, minimal, self-contained, reproducible code. >>> > >>> >>> >>> >>> -- >>> Ista Zahn >>> Graduate student >>> University of Rochester >>> Department of Clinical and Social Psychology >>> http://yourpsyche.org >>> >>> ______________________________________________ >>> R-help@r-project.org mailing list >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide http://www.R-project.org/posting- >>> guide.html >>> and provide commented, minimal, self-contained, reproducible code. >> > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.