Rank correlation is a statistical measure that assesses the strength and direction of the relationship between two variables based on their ranks rather than their actual values. It helps to determine how well the relationship between two sets of data can be described using their ranks, making it useful for non-parametric data. The most common methods for calculating rank correlation are Spearman's rank correlation coefficient and Kendall's tau. These methods provide a value between -1 and 1, where 1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 suggests no correlation.