This project leverages data from the National Transportation Safety Board (NTSB) repository to conduct a structured, data-driven investigation of aviation accidents across the United States. It employs Exploratory Data Analysis (EDA), hypothesis testing, and feature extraction to uncover meaningful patterns and correlations within the data. The analysis focuses on key variables such as: Aircraft Type – to assess how different models or categories influence accident likelihood. Flight Purpose – to evaluate operational contexts (commercial, private, training, etc.) associated with incidents. Weather Conditions – to determine the impact of environmental factors on accident occurrence. Time of Day – to identify temporal patterns in aviation risks. Geographical Location – to map and analyze region-specific trends. By statistically examining these factors, the project aims to identify significant aviation risk drivers that contribute to the frequency and severity of accidents. The findings are designed to provide evidence-based recommendations for aviation authorities, operators, and policymakers, enhancing decision-making processes related to flight safety. Beyond offering a retrospective analysis, the study lays the foundation for future predictive modeling, enabling proactive safety measures and bridging existing gaps in aviation risk management.

Dynamic map of regional connectivity based on the Greater Horseshoe Bat's movements. Reference : Pinaud, D., Varoux, M., Leuchtmann, M., & Pontier, D. (2025). Modelling connectivity at a regional scale during seasonal movements of the greater horseshoe bat. Journal of Applied Ecology, 00, 1–14. http://doi.org/10.1111/1365-2664.70115

Analisis ekonometrika tentang bagaimana ukuran kota kelahiran memengaruhi pendapatan individu, menggunakan model upah dan elastisitas populasi. Artikel ini merupakan bagian dari https://microeconr.netlify.app/

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