Conclusions

ARM was instrumental in identifying potential relationships between various factors, such as the origin state, that might be associated with flight delays due to weather. The rules generated by ARM not only indicated which factors are associated but also provided support through a lift score greater than 1, signifying a correlation between the variables. 

Furthermore, the results revealed that airlines like Envoy Air, originating from Illinois during cold temperatures, are susceptible to weather delays. A surprising observation was that flight delays in warm temperatures surpassed those in cool and cold temperatures. Upon further investigation, one of the main reasons identified was that warmer air is less dense than cooler air, potentially impacting aircraft engine performance and overall flight schedules. 

Additionally, future applications of ARM could explore optimal conditions for flights to run without weather delays or with minimal impact. The inclusion of factors such as humidity levels may yield more fruitful results. 

In conclusion, ARM proved to be a valuable tool for uncovering associations between factors influencing weather-related flight delays. The specific findings, like the vulnerability of certain airlines to various temperatures, provide practical insights. Looking ahead, there is potential for further research to enhance our understanding of optimal conditions and additional factors contributing to flight punctuality.