There were drones, there were boats. There were spotters on land and a hydrophone listening for suspicious sounds underwater. In what may have been the biggest search of its kind in 50 years, crowds of people gathered this summer in Scotland to hunt for any sign of a legendary creature: the Loch Ness Monster.
Nearly 6,000 kilometers away, data scientist Floe Foxon emailed the event’s organizers and wished them good luck. “I’m sure it’s going to be a fun weekend,” he said. Foxon wasn’t joining them, but from his home office in Pittsburgh, he has examined Nessie’s lore in his own way — with statistics.
In July, Foxon published a study on the probability of finding a giant eel in the loch, one of many hypotheses for sightings of the storied sea monster. The answer: Essentially zero. Even the chances of finding a 1-meter-long eel are low, about 1 in 50,000, Foxon reported in JMIRx Bio. But once you get much longer than that — into monster-sized eel territory — the probability plummets.
But don’t call Foxon a myth buster or a debunker. “Absolutely not,” he says. “I think you should approach these things with an open mind and let the data influence your decision-making.”
Though monsters have captured Foxon’s imagination, his background is in physics, and by day, he’s a data analyst for a health consulting firm. In his free time, he flits through far-flung fields of science, including astronomy, paleontology and cryptology, the study of ciphers. “When you learn data science,” Foxon says, “you find that it can be applied to more or less anything.” Even monsters.
For his Nessie study, Foxon analyzed the mass distribution of eels caught in Loch Ness and other freshwater bodies in Europe. He converted that data to eel length and then calculated the odds of finding eels of different sizes. And in a separate monster study posted online July 20 at biorXiv.org, Foxon looked at data on Big Foot sightings and black…
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