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Joint Probability - Python Automation and Machine Learning for ICs - - An Online Book - |
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| Python Automation and Machine Learning for ICs http://www.globalsino.com/ICs/ | ||||||||
| Chapter/Index: Introduction | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | Appendix | ||||||||
================================================================================= Joint probability refers to the probability of the occurrence of two (or more) events simultaneously. The joint probability of events A and B is denoted by P(A∩B), P(A, B) or P(A and B). For joint probability, we have, P(A and B) = P(B and A) ------------------------------------ [3604a] P(A and B) = P(A) x P(B|A) ------------------------------------ [3604b] P(B and A) = P(B) x P(A|B) ------------------------------------ [3604c] Then, we can obtain Bayes' Theorem,
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------------------------------------ [3604d]