The Windy City’s Dark Side: A Statistical Exploration of Crime in the City of Chicago

Odooh, Clement and Olisah, Somtobe and Onwuchekwa, Jane and Owolabi, Omoshola and Yufenyuy, Sevidzem Simo and Aderibigbe, Oluwadare and Obunadike, Echezona and Efijemue, Oghenekome and Akintayo, Saheed and Edozie, Samson (2024) The Windy City’s Dark Side: A Statistical Exploration of Crime in the City of Chicago. Journal of Data Analysis and Information Processing, 12 (03). pp. 370-387. ISSN 2327-7211

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Abstract

This paper presents a detailed statistical exploration of crime trends in Chicago from 2001 to 2023, employing data from the Chicago Police Department’s publicly available crime database. The study aims to elucidate the patterns, distribution, and variations in crime across different types and locations, providing a comprehensive picture of the city’s crime landscape through advanced data analytics and visualization techniques. Using exploratory data analysis (EDA), we identified significant insights into crime trends, including the prevalence of theft and battery, the impact of seasonal changes on crime rates, and spatial concentrations of criminal activities. The research leveraged a Power BI dashboard to visually represent crime data, facilitating an intuitive understanding of complex patterns and enabling dynamic interaction with the dataset. Key findings highlight notable disparities in crime occurrences by type, location, and time, offering a granular view of crime hotspots and temporal trends. Additionally, the study examines clearance rates, revealing variations in the resolution of cases across different crime categories. This analysis not only sheds light on the current state of urban safety but also serves as a critical tool for policymakers and law enforcement agencies to develop targeted interventions. The paper concludes with recommendations for enhancing public safety strategies and suggests directions for future research, emphasizing the need for continuous data-driven approaches to effectively address and mitigate urban crime. This study contributes to the broader discourse on urban safety, crime prevention, and the role of data analytics in public policy and community well-being.

Item Type: Article
Subjects: EP Archives > Computer Science
Depositing User: Managing Editor
Date Deposited: 06 Jul 2024 10:25
Last Modified: 06 Jul 2024 10:25
URI: http://research.send4journal.com/id/eprint/3987

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