Spearman Rank Correlation is used when you want to measure the strength and direction of a monotonic relationship between two variables, especially when:

1. The data is ordinal or ranked: If your data is in ranks or can be meaningfully ordered but not necessarily evenly spaced (e.g., survey rankings, Likert scale responses).
2. The relationship is not linear: Spearman correlation captures monotonic relationships that might not be linear (unlike Pearson correlation, which assumes linearity).
3. Data does not meet parametric assumptions: When data is not normally distributed or when you have outliers that could distort Pearson’s correlation.
4. You want a non-parametric measure: Spearman is a non-parametric test, so it doesn't assume the data comes from a particular distribution.