Abstract
In this report we will be investigating two datasets and calculating their statistical quantities for the interarrival times of incoming flights at DFW airport. This set contains the flight arrival time information of flights between roughly 6:00 AM and 12:30 PM on September 12th, 2022. The data was collected from the website by copying, pasting, and manually formatting the text provided by it. Our team believes that flights happened in a pattern which will follow an exponential distribution when graphed. We extrapolated and formatted the data based on the given flight times and presented it in tables and graphs to better visualize the data. While doing this has not confirmed our hypothesis, it shows promising similarities to our expectations and merits further testing. The main Grand Challenge that this and other datasets take on is restoring and improving urban infrastructure. The main SDGs it serves is industry, innovation, and infrastructure, as well as sustainable cities and communities. All the datasets can be used to advance infrastructure. Improving energy efficiency can lower expenses for everyone, lower emissions, and allow for other areas of infrastructure to be taken care of. Identifying trends in inter-arrival times will inform the global infrastructure to account for changes in travel demand, allowing business, leisure, and trade, etc. to continue with minimal problems and efficient spending.
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