# [R] How to find more about Covariance (in R)

Alaios alaios at yahoo.com
Wed Jan 19 15:59:51 CET 2011

```Dear Josh,

I think that it is clear that I miss a lot of theory. I have tried in google to read and study more about covariance but I have this feeling that the term 'covariance' is used for many different things in different topics.

You mentioned for example population and sample (covariance) which are two words-terms that I can not distinguish between them.

Even though this is R list could you please provide me some differences to study more about covariance before trying to implement things in R.

(Even in R are some things that do not understand i.e pearson, kendal and spearman method)

Best Regards
Alex

--- On Wed, 1/19/11, Joshua Wiley <jwiley.psych at gmail.com> wrote:

> From: Joshua Wiley <jwiley.psych at gmail.com>
> Subject: Re: [R] How to find more about Covariance (in R)
> To: "Alaios" <alaios at yahoo.com>
> Cc: r-help at stat.math.ethz.ch
> Date: Wednesday, January 19, 2011, 2:36 PM
> Hi Alex,
>
> cov() uses the formula for a sample covariance.  The
> denominator is N
> - 1 instead of N.  However, the formula you used from
> Wikipedia is for
> a population covariance.  To move between the two in
> this case:
>
> cov(sr, sr) * (4/5) # should equal E[XX] - E[x] * E[x]
>
> Cheers,
>
> Josh
>
> On Wed, Jan 19, 2011 at 6:29 AM, Alaios <alaios at yahoo.com>
> wrote:
> > Hello everyone,
> > I am trying to understand how covariance work. So I
> created a vector called sr<-c(2,5,7,5,2)
> >
> > so according to wikipedia Cov(X,X)=E[XX]-E[x]*E[x]
> which in R is
> >
> >
> > mean(sr*sr)-mean(sr)*mean(sr)
> > [1] 3.76
> >
> > but also
> >
> > cov(sr,sr)
> > [1] 4.7
> >
> > why is this difference between these two approaches?
> Where I am wrong?
> >
> > I would like to thank you in advance for your help
> >
> > Best Regards
> > Alex
> >
> > ______________________________________________
> > R-help at r-project.org
> mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > and provide commented, minimal, self-contained,
> reproducible code.
> >
>
>
>
> --
> Joshua Wiley
> Ph.D. Student, Health Psychology
> University of California, Los Angeles
> http://www.joshuawiley.com/
>

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