Abstract
The scales of measure for quantifying features of cases used in original recording of the data must obviously have some interpretive appeal; otherwise, they would not be used for recording the data in the beginning. In any case, the data as recorded on the original scales provide the starting point for rescaling to gain some comparative interpretive advantage. We pursue a structural scaling sequence of successive statistical simplification. In so doing, we focus on variability because variability consists of information and noise with (white) noise being variability that is lacking in pattern (independently random). A fairly crude gauge of variability is range as difference between maximum and minimum. Maximum and minimum are given in the default summary of a data frame provided by R.
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Myers, W.L., Patil, G.P. (2012). Suites of Scalings. In: Multivariate Methods of Representing Relations in R for Prioritization Purposes. Environmental and Ecological Statistics, vol 6. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3122-0_2
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DOI: https://doi.org/10.1007/978-1-4614-3122-0_2
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