Using Descriptive Analysis to Find Patterns and Trends: A Case of Car Accidents in Washington D.C.

The descriptive analysis could be used to find the trends and patterns in historical data. In this article, descriptive analysis has been used to describe the car accidents in Washington, D.C., between 2009 and 2020. The dataset was downloaded from the District Department of Transportation (DDOT), the department responsible for car accidents in Washington, D.C. Multiple analytics and statistical models have been applied to find the relationships between different variables and the patterns and trends among the data, such as correlation analysis, confidence interval, One-Way-ANOVA, decision tree, and visualizations. The article aims to find the common reasons for accidents and help DDOT find ways to reduce and eliminate accidents in the area. The statistical and analytical tools examine multiple features to find the patterns and trends among the datasets. Four main findings were found after analyzing the data. First, the main reason for most crashes is drunken people, either drivers or pedestrians. The second finding is that the top reason which causes deadly accidents is speed. Also, we have found that most of the accidents are not dangerous. In addition, we found the top ten streets that contain the highest accident number, and we found that they are located on the north side of the town.

@article{Altukhi2023,
  title     = {Using Descriptive Analysis to Find Patterns and Trends: A Case of Car Accidents in Washington D.C.},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {14},
  number    = {5},
  year      = {2023},
  publisher = {The Science and Information Organization},
  author    = {Zaid M. Altukhi and Nasser F. Aljohani},
  doi       = {10.14569/IJACSA.2023.0140527},
  url       = {https://doi.org/10.14569/IJACSA.2023.0140527}
}