In what scenarios would it be more appropriate to use Kendall's Tau over Spearman's correlation coefficient?

Datasets with many tied ranks
Datasets with normally distributed data
Datasets without outliers
Large datasets with ordinal data

It might be more appropriate to use Kendall's Tau over Spearman's correlation coefficient in scenarios with datasets with many tied ranks. Kendall's Tau is better at handling ties than Spearman's correlation coefficient. It's often used in scenarios where the data have many tied ranks.

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