In another usage in statistics, normalization refers to the creation of shifted and scaled versions of statistics, where the intention is that these "'normalized values "'allow the comparison of corresponding normalized values for different datasets in a way that eliminates the effects of certain gross influences, as in an anomaly time series.
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In another usage in statistics, normalization refers to the creation of shifted and scaled versions of statistics, where the intention is that these "'normalized values "'allow the comparison of corresponding normalized values for different datasets in a way that eliminates the effects of certain gross influences, as in an anomaly time series.
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These improvements, proposed initially by Dr . Jang Ra ( a student of Dr . Thomas L . Saaty who developed and refined AHP ) include the constant-sum measurement scale ( 1 99 scale ) for comparing two elements, the logarithmic least squares method ( LLSM ) for computing normalized values, the sum of inverse column sums ( SICS ) for measuring the degree of ( in ) consistency, and sensitivity analysis of pairwise comparisons matrices.
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