A Bayesian Interpretation of Two Deaths

What is the probability of Steve Chamberlain and Mike Lynch accidentally dying within the same 48-hour period?

Stephen "Steve" Chamberlain, 52, was struck by a car in Cambridgeshire, England, on Saturday, August 17 at around 10:10 a.m. Less than 48 hours later, Chamberlain’s former business partner, Mike Lynch, apparently drowned when his super yacht named Bayesian sank while at anchor off the coast of Sicily.

Chamberlain and Lynch were co-defendants in a U.S. trial over their tech company Autonomy. Both men were accused of fraud and conspiracy over allegedly inflating their company's earnings to secure an $11 billion deal with Hewlett-Packard. Both were acquitted of all 15 charges in June by a San Francisco jury.

The Bayesian was named after a statistical method for assessing probability, formulated by the 18th century British mathematician and presbyterian minister, Thomas Bayes.

Bayes' Theorem is a mathematical formula for calculating conditional probability—that is, the likelihood of an outcome occurring based on a previous outcome in similar circumstances. Bayes' Theorem is tool for updating existing probability assessments given new or additional evidence.

A probability assessment based entirely on the frequency or propensity of cyclists getting struck by cars in Cambridgeshire and modern super yachts sinking in freak weather events in the Med would probably find that the chance of these two men randomly dying in these unusual ways within 48 hours of each other to be less than 1 in a billion. I’ll leave it to pro statisticians to compile the data and do the proper math on this one.

However, if investigators find grounds for suspecting Steve Chamberlain’s death was no accident, but staged to look like one, this could enable investigators to perform a Bayesian interpretation of the probability of Mike Lynch’s yacht sinking 48 hours later. If it is determined that someone had an interest in eliminating Steve Chamberlain, this raises the probability that Lynch’s subsequent death was related to Chamberlain’s and was also no accident.

A Bayesian interpretation performed at the time Chamberlain was struck could have warranted alerting Mike Lynch (and his guests on the yacht) that a their lives were in danger and that extraordinary security measures should be taken to secure the vessel.

I hasten to add that the above reflections are more a matter of intuition than a proper understanding of how to perform a Bayesian probability assessment. I welcome the pro statisticians among our readers to chime in with their expertise.