The show is named for Charles Spearman, who developed Spearman's rank correlation coefficient, the statistical technique used to survey the public to produce the show's rankings.
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A rank correlation coefficient can measure that relationship, and the measure of significance of the rank correlation coefficient can show whether the measured relationship is small enough to likely be a coincidence.
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A rank correlation coefficient can measure that relationship, and the measure of significance of the rank correlation coefficient can show whether the measured relationship is small enough to likely be a coincidence.
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Some correlation statistics, such as the rank correlation coefficient, are also invariant to monotone transformations of the marginal distributions of " X " and / or " Y ".
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In continuous distributions, the grade of an observation is, by convention, always one half less than the rank, and hence the grade and rank correlations are the same in this case.
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The sum \ sum a _ { ij } b _ { ij } is twice the number of concordant pairs minus the number of discordant pairs ( see Kendall tau rank correlation coefficient ).
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The Kendall tau rank correlation coefficient, which measures how closely related two series of numbers are, is proportional to the difference between the number of concordant pairs and the number of discordant pairs.
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An estimate of Goodman and Kruskal's gamma, another measure of rank correlation, is given by the ratio of the difference to the sum of the numbers of concordant and discordant pairs.
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In statistics, the "'Page test "'for multiple comparisons between ordered correlated variables is the counterpart of Spearman's rank correlation coefficient which summarizes the association of continuous variables.
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While the Fisher transformation is mainly associated with the Pearson product-moment correlation coefficient for bivariate normal observations, it can also be applied to Spearman's rank correlation coefficient in more general cases.
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