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I have some EXTREMELY noisy data (standard deviation a is greater than the mean), but plotting it with a 15 data point running average does well to get a visual indication of the trending. I want to see if any of my data sets are correlated, but standard correlation gives me very poor results due to the noisiness of the data (and the fact that I care about trends over scales on the order of hundreds of data points). I'm thinking of maybe just cranking the running average up to a few hundred data points and then running the correlation on those, but something makes me think that there might be a better way.

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