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In 18th century British clergyman Thomas Bayes invented what would later be known as Bayes' Theorem and considered by some to be "Pythagorean theorem of probability".
Today used in fields as diverse as Artificial Intelligence and Statistics the simple formula gained notoriety for seemingly strange and surprising answers, even to seemingly simple problems.
You might ask yourself:"That's all nice but why would I need something like that? I'm no mathematician or AI programmer."
But the fact that you are not an expert means you need it much more than them.
Knowledge is power. And in today's world filled with information it is harder than ever to make rational judgments.
For example, consider simple matter of drug test.
If it comes positive for 95 out of 100 proven drug users but it also comes positive for about 5 out of 100 proven nonusers, it could be considered pretty accurate.
After all it was wrong only five times in a hundred.
But there are much fewer users than nonusers. If, for example, just one in hundred was actually a drug user then the positive test would be correctly positive in just 16% of all cases.
If you were going by the test alone a lot of innocent people could get caught in the net.
And that is just one example of where you can, and should, use Bayes' theorem.
