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Spearman correlation is often used to evaluate relationships involving ordinal variables. For example, you might use a Spearman correlation to evaluate whether the order in which employees complete a test exercise is related to the number of months they have been employed.
Consequently, why would you use Spearman's rank?
Spearman's Rank correlation coefficient is a technique which can be used to summarise the strength and direction (negative or positive) of a relationship between two variables. The result will always be between 1 and minus 1. Create a table from your data. Rank the two data sets.
One may also ask, what does Spearman correlation mean?
Spearman's correlation measures the strength and direction of monotonic association between two variables. Monotonicity is "less restrictive" than that of a linear relationship. However, you would normally pick a measure of association, such as Spearman's correlation, that fits the pattern of the observed data.
Pearson's Correlation Coefficient. Correlation is a technique for investigating the relationship between two quantitative, continuous variables, for example, age and blood pressure. For correlation only purposes, it does not really matter on which axis the variables are plotted.