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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?



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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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