So a Reverend called Thomas Bayes in the 1700s said that the probability of an event is based on prior knowledge of conditions that might be related to that event. Sounds weird. Right? This is Bayes Theorem (also called Bayes Law or Bayes Rule). Hold on, it gets weirder.

When you do an internet search for “movie automatic shoelaces” brings up “Back to the future”. Has google watched the movie? No. But it knows a lot about other searches. So Google knows what people are probably looking for. That how Google accurately gets “that movie where the guy smells food and has a flashback.” It is a weird mix of logic and probability, let us do an example:

1. Exploding batteries are rare (1%)

2. Overheating is fairly common in electrical appliances (10%)

3. Exploding batteries come from overheating. (90%)

Plugin the formula and you get that the probability of a battery exploding when there is overheating is 9%

It works well on human behavior too. For example, if the risk of developing health problems is known to increase with age, Bayes’ theorem allows the risk to an individual of a known age to be assessed more accurately (by conditioning it on their age) than simply assuming that the individual is typical of the population as a whole.

Having said that. Take a look at this image by XKCD. Your mind will wander between probability and prior knowledge. There lies the humor.

Image by Matt Buck

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