The 2009 ASA Statistical Computing and Graphics Data Expo consisted of flight arrival and departure details for all commercial flights on major carriers within the USA from October 1987 to April 2008. This is a large dataset; there are nearly 120 million records in total, and it takes up 1.6 gigabytes of space when compressed and 12 gigabytes when uncompressed.
The complete dataset, along with supplementary information and variable descriptions, can be downloaded from the Harvard Dataverse at https://doi.org/10.7910/DVN/HG7NV7 Choose any subset of ten consecutive years and any of the supplementary information provided by the Harvard Dataverse to answer the following questions using the principles and tools you have learned in this course:
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(a) What are the best times and days of the week to minimise delays each year?
(b) Evaluate whether older planes suffer more delays on a year-to-year basis.
(c) For each year, fit a logistic regression model for the probability of diverted US flights using as many features as possible from attributes of the departure date, the scheduled departure and arrival times, the coordinates and distance between departure and planned arrival airports, and the carrier. Visualize the coefficients across years.
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