Spearman's rank correlation is a statistical measure that assesses the strength and direction of the relationship between two ranked variables. Unlike Pearson's correlation, which requires data to be normally distributed, Spearman's correlation works with ordinal data or non-parametric data, making it more versatile for various types of datasets. To calculate Spearman's rank correlation, each value in the datasets is replaced by its rank, and then the correlation coefficient is computed based on these ranks. The result ranges from -1 to +1, where -1 indicates a perfect negative correlation, 0 means no correlation, and +1 signifies a perfect positive correlation.