What is the Bayes Theorem and why is it useful?
In: Mathematics
Bayes Theorem is a way to weight evidence by the strength of the evidence. Say you have a coin and you think it’s not a perfect 50/50 chance when you flip it. If you test it comes up heads twice, do you assume it has a 100% chance to land heads? No, but your data is saying it’s 100% heads. So you use Bayes Theorem to adjust the observed data by your prior assumption. Assume any random coin is 50/50 and adjusting your expectation as you collect more data from additional coin flips. The more data you collect the more confident you can be that your data represents a true deviation from an average coin.
It’s very useful for making statistical predictions because it makes a distinction between an Observed Probability and the true underlying probability of something happening by factoring in the likelihood that the observed data could have just occurred randomly.
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