one. Using the variables stated inside the table over, state for every variable whether it is qualitative or quantitative; if it is qualitative, condition whether it is nominal or ordinal, and if it is quantitative, condition whether it's discrete or constant.
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I've listened to the "square" described variously as a means to set special emphasize on substantial deviations in one factors about smaller deviations in many, or stated to be a way to get a favourable convex assets in the minimization challenge. Are any of those explanations appropriate and/or worth maintaining in mind when working with the mahalanobis length?
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