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What is conditioning on evidence?

  • A.Removing the evidence variables from the model entirely
  • B.Adjusting the prior until it matches the observed data
  • C.Restricting attention to the outcomes consistent with the evidence
  • D.Multiplying every probability by the probability of the evidence

Answer: C

Conditioning discards the outcomes inconsistent with what was observed and renormalises the rest, which is exactly what Bayes' rule computes. Multiplication by the evidence probability would be division, removal loses information and prior adjustment is a different operation. Understanding conditioning as restriction plus renormalisation makes the rule intuitive rather than a formula to be memorised.

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