Analysis of the Causes of Car Accidents in the United States of America in 2023: Gauge People Understanding of Data Visualisation

TL;DR

This study evaluates how interactive data visualizations impact understanding of US car accident data in 2023, revealing that effectiveness varies by visualization type and interactivity, with some static visuals outperforming interactive ones.

Contribution

It introduces an assessment of interactive versus static visualizations for car accident data comprehension, highlighting the nuanced effectiveness of different visualization types.

Findings

Interactive heatmaps improve data understanding.

No significant difference between static and interactive histograms.

Static pie charts outperform interactive ones.

Abstract

This paper presents a comprehensive examination of interactive data visualization tools and their efficacy in the context of United States car accident data for the year 2023. We developed interactive heatmaps, histograms, and pie charts to enhance the understanding of accident severity distribution over time and location. Our research included the creation and distribution of an online survey, consisting of nine questions designed to test participants comprehension of the presented data. Fifteen respondents were recruited to complete the survey, with the intent of assessing the effectiveness of both static and interactive versions of each visualization tool. The results indicated that participants using interactive heatmaps showed a greater understanding of the data, as compared to those using histograms and pie charts. In contrast, no notable difference in comprehension was observed between users of static and interactive histograms. Unexpectedly, static pie charts were found to be slightly more effective than their interactive counterparts. These findings suggest that while interactive visualizations can be powerful, their utility may vary depending on the type and complexity of the data presented. Future research is recommended to explore the influence of socioeconomic factors on the understanding of car accident data, potentially leading to more tailored and effective visualization strategies. This could provide deeper insights into the patterns and causes of car accidents, facilitating better-informed decision-making for stakeholders. Visit our website to explore our interactive plots and engage directly with the data for a more comprehensive understanding of our findings.