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-μ)/σ, where μ is the populace mean and σ would be the populace conventional deviation. This can be a dimensionless amount which you can interpret as the volume of regular deviations that x
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The more attention-grabbing graphic will be the geometry with the Cholesky transformation, which standardizes and "uncorrelates" the variables.
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Quite a few discriminant algorithms use the Mahalanobis length, or You can utilize logistic regression, which would be my decision. Although you could possibly do it "by hand," you would probably be much better off working with a conventional algorithm. If you need help, article your query and sample knowledge towards the SAS Guidance Communities.
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