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Bayes’ Rule and Coast Guard Rescues

Probability is applicable to practically every aspect of our lives, and whether we realize it or not, probability calculations are behind so many of our everyday decisions. The power of probability can also be harnessed for more large-scale, important applications. One particularly fundamental concept in probability is Bayes’ Rule, which uses conditional probability to determine the probability of an event occurring based on prior knowledge of the probability of other relevant events. Bayes’ Rule has been used for diverse and numerous applications, and the U.S. Coast was even able to apply it to save a fisherman who was lost at sea. In 2014, John Aldridge was catching lobster near the coast of Long Island when he fell overboard and was lost at sea.

To find him, the Coast Guard utilized a software system called SAROPS (Search and Rescue Optimal Planning System). SAROPS uses Bayes’ Rule to create a probability map of the potential areas in which someone lost at sea could be located. According to Bayes’ Rule, the probability of an event X occurring based on an event Y having occurred is calculated as follows:

In this case, SAROPS uses data on information such as the timeframe of the disappearance, ocean currents in the general vicinity, and wind patterns to calculate the conditional probability of a surviving being located in each specific location on the map. With this probability map calculated using Bayes’ Rule, SAROPS was able to lead the Coast Guard to Aldridge’s location in the ocean and rescue him. Thus, Bayes’ Rule has applications that extend beyond just mathematical theory, and in this instance, even helped to save a life.


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October 2018