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In statistics, Spearman's rank correlation coefficient or Spearman's ρ, named after Charles Spearman [1] and often denoted by the Greek letter (rho) or as , is a nonparametric measure of rank correlation (statistical dependence between the rankings of two variables).
Spearman’s correlation in statistics is a nonparametric alternative to Pearson’s correlation. Use Spearman’s correlation for data that follow curvilinear, monotonic relationships and for ordinal data. Statisticians also refer to Spearman’s rank order correlation coefficient as Spearman’s ρ (rho).
Spearman’s rho, or Spearman’s rank correlation coefficient, is the most common alternative to Pearson’s r. It’s a rank correlation coefficient because it uses the rankings of data from each variable (e.g., from lowest to highest) rather than the raw data itself.
Spearman’s Rank Correlation is a statistical measure of the strength and direction of the monotonic relationship between two continuous variables. Therefore, these attributes are ranked or put in the order of their preference. It is denoted by the symbol “rho” (ρ) and can take values between -1 to +1.
The Spearman rank correlation coefficient, \(r_s\), is a nonparametric measure of correlation based on data ranks. It is obtained by ranking the values of the two variables ( X and Y ) and calculating the Pearson \(r_p\) on the resulting ranks, not the data itself.
The Spearman rank correlation coefficient, r s, is the nonparametric version of the Pearson correlation coefficient. Your data must be ordinal, interval or ratio. In addition, because Spearman’s measures the strength of a monotonic relationship, your data has to be monotonically related.
The Spearman's rank-order correlation is the nonparametric version of the Pearson product-moment correlation. Spearman's correlation coefficient, (ρ, also signified by r s ) measures the strength and direction of association between two ranked variables.
This type of correlation analysis is also known as Spearman rank order correlation or Spearman rank correlation coefficient. Like Pearson and partial correlations, Spearman rank correlation values range between −1 and +1.
The Spearman rank correlation coefficient, also known as Spearman's rho, is a nonparametric (distribution-free) rank statistic proposed by Spearman in 1904 as a measure of the strength of the associations between two variables (Lehmann and D'Abrera 1998).
The Spearman rank correlation coefficient (Spearman ρ) is a nonparametric measurement correlation. It is used to determine the relation existing between two sets of data. Spearman, Charles was a psychologist. In 1904 he introduced for the first time the rank correlation coefficient.