Spearman's rank correlation coefficient is a measure of a monotone association that is used when the distribution of data makes Pearson's correlation coefficient undesirable or misleading.
Spearman's coefficient is not a measure of the linear relationship between two variables, as some "statisticians" declare.
It assesses how well an arbitrary monotonic function can describe a relationship between two variables, without making any assumptions about the frequency distribution of the variables.
Unlike Pearson's product-moment correlation coefficient, 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.
Spearman's rank correlation coefficient is a measure of a monotone association that is used when the distribution of data makes Pearson's correlation coefficient undesirable or misleading.
Spearman's coefficient is not a measure of the linear relationship between two variables, as some "statisticians" declare.
It assesses how well an arbitrary monotonic function can describe a relationship between two variables, without making any assumptions about the frequency distribution of the variables.
Unlike Pearson's product-moment correlation coefficient, 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.