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I am confused how to interpret the result of preforming a normalized correlation with a constant vector. Since you have to divide by the standard devation of both vectors (reference: http://en.wikipedia.org/wiki/Cross-c...ss-correlation ) , if one of them is constant (say a vector of all 5's, which has standard deviation=0), then the correlation is infinity, but in fact the correlation should be zero right? This isn't just a corner case, in general if the standard deviation of one of the vectors is small, the correlation to any other vector is very high. Can anyone explain my misinterpretation?

Thanks,

David

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You might have a better chance of getting a good answer at stats.stackexchange.com . –  Angelo Feb 26 '12 at 4:57
    
The covariance is $0$, the correlation is undefined. Correlations (when defined) are always in the interval $[-1,1]$. –  Robert Israel Feb 26 '12 at 18:23

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