```Date: Sun, 11 Dec 2005 07:34:35 -0500 Reply-To: Peter Flom Sender: "SAS(r) Discussion" From: Peter Flom Subject: Re: Normality Assumption for Pearson Product Moment Correlation Comments: To: davidlcassell@MSN.COM Content-Type: text/plain; charset=US-ASCII > David L Cassell >>> 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 ```

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