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Spearman's rank correlation coecient (denoted here by rs) is a non- parametric (distribution-free) rank statistic proposed by Charles Spearman as a measure of the strength of the associations between two variables. It is a measure of a monotone association that is used when the distribution of the data makes Pearson's correlation coecient undesirable or misleading. Spearman's coecient is not a measure of the linear relationship between two variables, as some "statisticians" declare. It assesses how well an arbi- trary monotonic function can describe the relationship between two variables, without making any assumptions about the frequency distribution of the vari- ables. Unlike Pearson's product-moment correlation coecient, it does not require the assumption that the relationship between the variables is linear, nor does it require the variables to be measured on interval scales; it can be used for variables measured at the ordinal level. In principle, rs is simply a special case of Pearson's product-moment coecient

Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of Data