# The Correlation between Users' Cognitive Characteristics and Visualization Literacy
## 6 Discussion
### Discussion on the Correlation  
The goal of this study was to investigate the correlation between user cognitive characteristics and visualization literacy. We focused on numeracy, need for cognition, and visualizer-verbalizer style in the scope of this study. Our results confirmed that an individual's numeracy and need for cognition has a positive correlation with his/her visualization literacy, but visualizer-verbalizer cognitive style does not. Our study shows that numeracy correlates positively with visualization literacy. Users with high-numeracy had significantly high visualization literacy scores (on average, it was approximately 50% higher). It indicates that an individual who is good at understanding, using, and processing numerical information would be likely to be good at reading and interpreting data visualizations. This is consistent with a finding in the context of health risk assessment tasks with bar charts and icon arrays from [PERSON] and [PERSON] (2014). Perhaps it is an inevitable result because data visualizations are graphically transformed forms of numerical data ([PERSON] and [PERSON], 2016). In particular, we may also speculate possible reasons that low-numeracy users may perform poorly at certain visualization tasks that require numerical manipulation (e.g., Determine Range, Make Comparisons, and Find Correlations/Trends). Low-numeracy users may not have established a proper understanding of visual encoding schemes for certain data visualizations (e.g., Bubble Chart) and thus may be inaccurate in carrying out visualization tasks. Low-numeracy users may also neglect crucial numerical information on data visualizations. Low-numeracy users may simply not be interested in visually represented numerical data. Our additional findings in Section 5.5 allude to these speculations further. In addition to numeracy, need for cognition also turned out to have a positive correlation with visualization literacy. However, the correlation between need for cognition and visualization literacy was not as high as that between numeracy and visualization literacy (numeracy and visualization literacy: [PERSON]'s \(d=1.07\); need for cognition and visualization literacy: [PERSON]'s \(d=0.32\)). Even though it has a medium-small effect size, this still indicates that if an individual tends to engage in and enjoy effortful cognitive endeavors, he/she would be good at reading and interpreting data visualizations. This finding is consistent with a recent study on a bar chart and a line chart ([PERSON] and [PERSON], 2016). According to literature on need for cognition (e.g., ([PERSON] and [PERSON], 2016; [PERSON] and [PERSON], 2016)), it is possible that high-need-for-cognition users may be motivated to extract information from visually represented data. In addition, high-need for cognition users may make fact-based judgments that are supported by underlying data. They may perhaps employ thorough seeking strategies while reading and interpreting data visualizations. Surprisingly we did not find a correlation between visualizer-verbalizer cognitive style and visualization literacy. The visualizers' ability to read and interpret data visualizations was no better than that of the verbalizers. This implies that an individual's preference to use and process a certain format of information does not have a positive/negative correlation with his/her visualization literacy. Even if an individual prefers visual information (e.g., graphs, diagrams, pictures) and relies on visual information while conducting cognitive tasks, he/she may not be good at reading and interpreting data visualizations. However, even if an individual prefers perceiving, processing, and using verbal information (e.g., text, words), he/she may be able to use data visualizations without any problems.