How Statisticians Found Air France Flight 447 Two Years After It Crashed Into Atlantic

After more than a year of unsuccessful searching, authorities called in an elite group of statisticians. Working on their recommendations, the next search found the wreckage just a week later. So begin Lawrence Stone and colleagues from Metron Scientific Solutions in Reston, Virginia, in describing their role in the discovery of the wreckage almost two years after the loss of the aircraft.

… Today, Stone and co explain how they did it. Their approach was to use a technique known as Bayesian inference which takes into account all the prior information known about the crash location as well as the evidence from the unsuccessful search efforts.

Bayesian inference is a statistical technique that mathematicians use to determine some underlying probability distribution based on an observed distribution. In particular, statisticians use this technique to update the probability of a particular hypothesis as they gather additional evidence.

The key point, of course, is that Bayesian inference by itself can’t solve these problems. Instead, statisticians themselves play a crucial role in evaluating the evidence, deciding what it means and then incorporating it in an appropriate way into the Bayesian model.

… Let’s hope that the assumptions used to update future searches for MH 370 are ultimately as successful as those that Stone and co employed in 2011.

Reference: How Statisticians Found Air France Flight 447 Two Years After It Crashed Into Atlantic

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