Predicting Next Fatal Airline Crash using Python

Welcome in 2019! Happy New Year, All!

Before the upcoming premiere of my new book Cryptocurrencies with Python, I decided to kick off this year at QuantAtRisk with my lecture I gave in May 2016 in Singapore. Staying in the circle of Python applications, I divert from the main stream in order to illustrate an appealing case study on predictive modelling and risk management. Enjoy watching and share your comments below!

Predicting Next Fatal Airline Crash Due to Bad Weather Conditions

Synopsis: Instrument meteorological conditions (IMC) is an aviation flight category that describes weather conditions that require pilots to fly primarily by reference to instruments, and therefore under instrument flight rules (IFR), rather than by outside visual references. We study the NTSB aviation accident database which contains information from 1962 and later about civil aviation accidents regarding all cases of fatal air crashes in the world due to bad weather conditions (IFR-based). Using classical and Bayesian statistics we build a model for effective calculation of the probability of the occurrence of next accident for the major airlines operating their flights with AIRBUS, BOEING, Embraer, and McDonnell Douglas types of aircrafts.

 

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