This project presents a statistical analysis and visualization of the Chicago crime dataset, aiming to explore crime trends between 2008 and 2018 and their relationship with factors such as unemployment, economic growth, and poverty. The study utilizes secondary data sources from Kaggle and the city of Chicago data repository, including information on crime incidents, location, and socio-economic indicators. The project addresses key questions regarding crime trends, the impact of unemployment and economic growth on crime rates, and the distribution of crime and poverty across Chicago communities. Through data exploration and visualization, the project seeks to uncover insightful relationships between crime and various factors, providing a comprehensive overview of the crime landscape in Chicago. The methodology involves both basic and advanced visualization techniques to reveal patterns and correlations within the data. The findings are presented in a dashboard format, summarizing key insights from the analysis.
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