Spearman's rank coefficient is primarily designed to measure the correlation between two sets of results, making it unsuitable for directly analyzing multiple sets simultaneously. To assess correlations among four sets of results, one approach is to calculate the Spearman's rank coefficient for each pair of sets individually. This method allows for a comprehensive understanding of relationships across all sets. Alternatively, other statistical methods, such as multivariate analysis, could be considered for a more holistic view of the data. Understanding the limitations of Spearman's rank coefficient is crucial for accurate data interpretation in biological experiments.