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Bayes’ Theorem is without doubt one of the most generally used and celebrated ideas in statistics. It units the idea of a likelihood principle that enables us to revise predictions or hypotheses primarily based on new proof.
In a earlier article on probability notation, I launched P(B∣A)— the likelihood of occasion B taking place provided that occasion A has already occurred.
Bayes’ Theorem flips this attitude, specializing in P(A∣B): the probability of A, provided that B has occurred. In essence, it helps us refine our understanding of outcomes by incorporating prior data (identified information).
In follow, even when your preliminary assumptions or estimates aren’t good, the method of making use of the Bayes’ theorem encourages extra considerate and knowledgeable guesses for the longer term!
To start with, let’s have a look at an instance impressed by the famous work of Daniel Kahneman and Amos Tversky.