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

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SUMMARY

The Law of Total Probability is established as a theorem, derived from the axiom that the probabilities of disjoint events can be summed. Specifically, if events A1, A2, ..., AN are disjoint and their union equals A, then the probability of A is the sum of the probabilities of the individual events. The theorem is further illustrated by expressing the probability of a subset B within A as a disjoint union, leading to the formula P(B) = ∑ P(B | An) P(An). This demonstrates the theorem's simplicity, relying on the substitution of definitions into established axioms.

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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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