Abstract Histograms are widely used and appear easy to understand. Research nevertheless indicates that students, teachers and researchers often misinterpret these graphical representations. Hence, the research question addressed in this paper is: What are the conceptual difficulties that become manifest in the common misinterpretations people have when constructing or interpreting histograms? To identify these conceptual difficulties, we conducted a narrative systematic literature review and identified 86 publications reporting or containing misinterpretations. The misinterpretations were clustered and—through abduction—connected to difficulties with statistical concepts. The analysis revealed that most of these conceptual difficulties relate to two big ideas in statistics: data (e.g., number of variables and measurement level) and distribution (shape, centre and variability or spread). These big ideas are depicted differently in histograms compared to, for example, case-value plots. Our overview can help teachers and researchers to address common misinterpretations more generally instead of remediating them each individually.

中文翻译：

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解释直方图时的概念困难：综述

摘要 直方图被广泛使用并且看起来很容易理解。尽管如此，研究表明学生、教师和研究人员经常误解这些图形表示。因此，本文解决的研究问题是：人们在构建或解释直方图时常见的误解中表现出哪些概念上的困难？为了确定这些概念上的困难，我们进行了叙述性系统文献回顾，并确定了 86 篇报道或包含误解的出版物。误解是聚集在一起的，并且——通过推断——与统计概念的困难有关。分析表明，这些概念上的困难大多与统计学中的两大思想有关：数据（例如，变量和测量级别的数量）和分布（形状、中心和可变性或分布）。例如，与案例值图相比，直方图中的这些重要想法的描述方式有所不同。我们的概述可以帮助教师和研究人员更广泛地解决常见的误解，而不是单独纠正它们。