In the present paper, we discuss the Pearson, Spearman, Kendall correlation coefficients and their statistical analogues. We propose a new correlation coefficient r and its statistical analogue. The coefficient r is based on Kendal's and Spearman's correlation coefficients. A new extension of the Pearson correlation coefficient is also discussed. We conduct simulation experiments and study the behavior of the above correlation coefficients. We observe that the behavior of Pearson's sample correlation coefficient can be very different from the behavior of the rank correlation coefficients, which, in turn, behave in a similar way. The question arises: which correlation coefficient better measures the dependence rate? We try to answer this question in the final conclusion.

翻译：本文讨论了Pearson、Spearman、Kendall相关系数及其统计对应量。我们提出了一种新的相关系数r及其统计对应量，该系数基于Kendall和Spearman相关系数构建。文中同时探讨了Pearson相关系数的一种新扩展。通过模拟实验，我们研究了上述相关系数的行为特征。实验表明：Pearson样本相关系数的行为可能与秩相关系数存在显著差异，而各秩相关系数之间则表现出相似行为。由此引出一个核心问题：何种相关系数能更有效地度量依赖程度？我们将在最终结论中尝试回答这一问题。