Date: Sun, 11 Dec 2005 07:34:35 0500
ReplyTo: Peter Flom <flom@NDRI.ORG>
Sender: "SAS(r) Discussion" <SASL@LISTSERV.UGA.EDU>
From: Peter Flom <flom@NDRI.ORG>
Subject: Re: Normality Assumption for Pearson Product Moment Correlation
ContentType: text/plain; charset=USASCII
> David L Cassell <davidlcassell@MSN.COM> >>> wrote
<<<
There's no normality assumption at all in the *calculation* of the
Pearson
r. The assumption comes in later, when you use that r and do the
hypothesis test of
H0: rho = 0. If you assume bivariate normality (and independence, and
equally distributed) then r is the best way to assess the strength of
the
relationship between the two variables. That's because the bivariate
normality
guarantees a linear relationship between the variables, and r is a
parametric measure
of rho.
>>>
I never heard before that bivariate normality assures a linear
relationship, and I'm having
a little trouble figuring out why it should.....
any pointers to articles or whatever discussing this?
Usually, I just stress that correlation is just a measure of LINEAR
relationship, and then
do scatterplot to see if it looks like there is a NONlinear
relationship, so this isn't really critical,
but I always like to learn things like this....
TIA
Peter
