Millistel juhtudel tasub Spearmani korrelatsiooni kasutada Pearsoni asemel?

Spearman correlation is used instead of Pearson correlation when the data do not meet the requirements of a normal distribution or when the dependence between variables is not linear but monotonic (i.e., variables change in the same direction but not necessarily linearly). Spearman is based on data ranks and is resistant to outliers and nonlinear monotonic relationships.

Examples of cases for Spearman:

• Data have strong outliers.
• The dependence between variables is monotonic but not linear (e.g., exponential or logarithmic).
• Data are ordinal or ranked.

While Pearson correlation is suitable for measuring linear dependence between quantitative variables with a normal distribution.