Halperin S
Psychoneuroendocrinology. 1986;11(1):3-13. doi: 10.1016/0306-4530(86)90028-4.
Although the Pearson Product--Moment Correlation Coefficient is one of the most widely used statistics in the health and behavioral sciences, it is not always appreciated that the critical assumption of bivariate normality underlies its interpretation. When variables have marginal distributions which are skewed or have heavy tails which produce outliers, correlations may be either spuriously large or small. Having diagnosed problems through exploratory data analysis, one must take the appropriate corrective action, such as re-expressing (transforming) variables or selectively discarding discordant observations.
尽管皮尔逊积矩相关系数是健康和行为科学中使用最广泛的统计量之一，但人们并不总是认识到双变量正态性这一关键假设是其解释的基础。当变量的边际分布呈偏态或具有产生异常值的重尾时，相关性可能会要么虚假地大要么虚假地小。通过探索性数据分析诊断出问题后，必须采取适当的纠正措施，例如重新表达（变换）变量或有选择地丢弃不一致的观测值。
