Welcome to the Jangle (Fallacy): The Case of Statistics and Mathematics Anxieties

Despite considerable academic interest in the construct of statistics anxiety, we know little about how it operates, or even what it is. Statistics anxiety is said to be distinct from mathematics anxiety, but existing evidence suffers methodological limitations and relies heavily upon correlations that cannot take subscale specificity into account. Yet, if statistics and mathematics anxieties are the same constructs (i.e., have fallen prey to the jangle fallacy), the statistics anxiety field could draw upon this advanced knowledge and extrapolate considerable empirical and theoretical insights. The present study addresses this, examining the extent to which statistics anxiety (as measured by the Statistics Anxiety Rating Scale; STARS) and mathematics anxiety (as measured by the Revised Mathematics Anxiety Rating Scale; R-MARS) overlap. Across three core analyses, each conducted in two samples (n = 489 and n = 245), we consistently evidence strong construct overlap. The factor analyses showed items from the scales did not load onto statistics or mathematics anxiety specific factors, the latent profile analyses showed it was very rare (< 2%) for an individual to have statistics anxiety but not mathematics anxiety, and our experimental studies revealed that individuals with statistics anxiety did not experience a greater increase in state anxiety when taking a statistics test than a mathematics test, or vice-versa. Counter to the narrative, our results suggest a jangle fallacy. Further research is needed, but statisitics anxiety researchers must be careful not to include both scales in their analyses to avoid collinearity issues and to consider that findings using these scales are equivalent.

尽管统计学焦虑这一构念引起了学术界的广泛关注，然而关于其运作机制乃至其本质，我们所知甚少。统计学焦虑与数学焦虑被声称是两种不同的构念，但现有的证据在方法论上存在局限，且过分依赖无法考虑子量表特异性的相关性。然而，如果统计学焦虑与数学焦虑是同一构念（即，均陷入了混淆谬误），那么统计学焦虑领域可以借鉴这一先进知识，并从中推演大量的实证与理论洞见。本研究旨在解决这一问题，探究统计学焦虑（以统计学焦虑评分量表（STARS）进行测量）与数学焦虑（以修订版数学焦虑评分量表（R-MARS）进行测量）之间重叠的程度。在三个核心分析中，每个分析都在两个样本（n = 489 和 n = 245）中展开，我们一致发现强烈的构念重叠。因子分析表明，量表中的项目并未加载到统计学或数学焦虑的特定因素上，潜在轮廓分析显示，个体在不存在统计学焦虑但存在数学焦虑的情况非常罕见（< 2%），而我们的实验研究揭示了具有统计学焦虑的个体在进行统计学测试时并未体验到比进行数学测试时更大的状态焦虑增加，反之亦然。与现有观点相反，我们的结果暗示了混淆谬误的存在。尽管需要进一步的研究，但统计学焦虑的研究者必须谨慎，避免在分析中同时包含这两个量表，以避免共线性问题，并考虑到使用这些量表所得出的发现具有等效性。