Bayes' Theorem: Intuition 1, Sets

What is Bayes' theorem and what is the intuition behind it?

Answer

The first intuition is thinking in terms of conditional probabilities (and sets):

\[ P(A \mid B) = \frac{P(A \cap B)}{P(B)} \quad \text{and} \quad P(B \mid A) = \frac{P(A \cap B)}{P(A)}. \]

Thus,

\[ P(A \cap B) = P(A \mid B)P(B) = P(B \mid A)P(A). \]

Rearranging gives Bayes' theorem:

\[ P(A \mid B) = \frac{P(B \mid A) P(A)}{P(B)}. \]
Notes and comments

Comment 1: Note that in exercises for the Bayes' Theorem we use the LOTP for the denominator.

Back to collection