Visualizations are common methods to convey information but also increasingly used to spread misinformation. It is therefore important to understand the factors people use to interpret visualizations. In this paper, we focus on factors that influence interpretations of scatter plots, investigating the extent to which common visual aspects of scatter plots (outliers and trend lines) and cognitive biases (people's beliefs) influence perception of correlation trends. We highlight three main findings: outliers skew trend perception but exert less influence than other points; trend lines make trends seem stronger but also mitigate the influence of some outliers; and people's beliefs have a small influence on perceptions of weak, but not strong correlations. From these results we derive guidelines for adjusting visual elements to mitigate the influence of factors that distort interpretations of scatter plots. We explore how these guidelines may generalize to other visualization types and make recommendations for future studies.

翻译：可视化是传递信息的常见手段，但也日益被用于传播错误信息。因此，理解人们解读可视化时依赖的因素至关重要。本文聚焦于影响散点图解读的因素，探究散点图的常见视觉方面（异常值和趋势线）与认知偏差（个人信念）在多大程度上影响相关性趋势的感知。我们提出三项主要发现：异常值会扭曲趋势感知，但其影响程度弱于其他数据点；趋势线使趋势显得更强，但同时也削弱了部分异常值的影响；个人信念对弱相关性的感知有轻微影响，但对强相关性则无显著作用。基于这些结果，我们推导出调整可视化元素的指导原则，以减轻扭曲散点图解读的因素之影响。我们探讨了这些原则如何推广至其他可视化类型，并为未来研究提出建议。