the interpretation of the spearman correlation coefficient is identical to that for the
Spearman's rank correlation coefficient The Spearman correlation between two variables is equal to the Pearson correlation between the rank values of those two variables; while Pearson's correlation assesses linear relationships, Spearman's correlation assesses monotonic relationships (whether linear or not). If there are no repeated data values, a perfect Spearman correlation of +1 or âˆ’1 occurs when each of the variables is a perfect monotone function of the other.
Correlation does not imply causation Reverse causation or reverse causality or wrong direction is an informal fallacy of questionable cause where cause and effect are reversed. The cause is said to be the effect and vice versa.