Pearson Correlation in Aviation Safety. A Comprehensive Analysis of Contributing Factors to Runway Excursions and Incursions

Runway excursions and incursions continue to be major concerns in aviation safety, leading to operational interruptions and possible risks. This study investigates the reasons behind these accidents by utilizing Pearson correlation analysis to examine the linkages between human error, environmental variables, technology systems, and regulatory frameworks. An extensive dataset that covers the years 1996 to 2024 and is based on aircraft safety reports from throughout the world was examined to determine the most important contributing elements. The results show that the most important factors that lead to runway excursions are communication breakdowns and sit uational awareness. Inadequate training and loss of control are the factors that have the strongest connection to incur sions. The findings indicate that by 2050, the implementation of AI-driven monitoring systems and standardized global safety measures might potentially decrease the ccurrence of these catastrophes by as much as 50%. The report offers useful information for politicians, airport management, and aviation safety agencies to improve safety initiatives. This research highlights the significance of making decisions based on data to enhance runway safety and reduce future risks. It does this by addressing the main contributing elements through advanced training, predictive analytics, and technological interventions.