Is the Law of Total Probability a Theorem or an Axiom?

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Discussion Overview

The discussion centers on whether the law of total probability should be classified as a theorem or an axiom. It explores the definitions and implications of both terms within the context of probability theory.

Discussion Character

  • Debate/contested

Main Points Raised

  • Some participants assert that the law of total probability is a theorem.
  • Others argue that it is an axiom, particularly emphasizing the axiom that allows the summation of probabilities of disjoint events.
  • A participant elaborates on the relationship between axioms and theorems, suggesting that the law of total probability can be derived from an axiom through substitution of definitions.
  • One participant expresses appreciation for the clarity of the explanation provided in the discussion.

Areas of Agreement / Disagreement

Participants do not reach a consensus, as there are competing views on whether the law of total probability is a theorem or an axiom.

Contextual Notes

The discussion involves assumptions about the definitions of the terms "theorem" and "axiom" in the context of probability, which may not be universally agreed upon.

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Is the law of total probability a theorem or an axiom?
 
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Theorem.
 
It is an axiom that the probabilities of disjoint events can be summed: if ##A_1, \ldots A_N## are disjoint and ##\bigcup_{n=1}^{N}A_n = A##, then ##P(A) = \sum_{n=1}^{N} P(A_n)##.

If ##B \subset A##, then we may write ##B## as the disjoint union ##B = \bigcup_{n=1}^{N} (B \cap A_n)##, so the axiom gives us ##P(B) = \sum_{n=1}^{N}P(B \cap A_n)##.

Finally, if ##P(A_n) > 0## we define ##P(B | A_n) = P(B \cap A_n) / P(A_n)##, so ##P(B \cap A_n) = P(B|A_n) P(A_n)##. Substituting into the result in the previous paragraph, we obtain
$$P(B) = \sum_{n=1}^{N} P(B|A_n) P(A_n)$$

So, it's a theorem, but quite a simple one: we simply substitute a definition into an axiom.
 
wow!
That is really very clear. :) Thanks.
 

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