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Module 2 · Probability Foundations · Topic 8

Bayes' Theorem

Intuition. Bayes’ theorem lets you reverse conditional probabilities. If you know P(B | A) and want P(A | B), Bayes’ theorem connects them using the prior probability P(A) and the total probability P(B).

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In the full lesson

  • Bayes' Theorem (formula)
  • Medical Test Example (example)
  • Base Rate Neglect (tip)

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Key formulas

From the Probability Foundations formula sheet

  • Conditional Probability: P(A | B) = P(A and B) / P(B) - Probability of A after restricting attention to cases where B occurred.
  • Bayes' Theorem: P(A | B) = P(B | A)P(A) / P(B) - Updates a prior probability after observing evidence.

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Related glossary terms

  • Independence: Two events are independent when one occurring does not change the probability of the other. Example: Two separate fair coin flips are independent.

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