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

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The law of total probability is considered a theorem derived from an axiom regarding the summation of probabilities of disjoint events. It states that if events A1, A2, ..., AN are disjoint and their union equals A, then the probability of A can be expressed as the sum of the probabilities of the individual events. Additionally, for a subset B of A, B can be represented as a disjoint union, allowing the application of the axiom to find the probability of B. The theorem further defines conditional probability, leading to the formula P(B) = Σ P(B|An) P(An). Ultimately, the law of total probability simplifies to a theorem based 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.
 
I was reading documentation about the soundness and completeness of logic formal systems. Consider the following $$\vdash_S \phi$$ where ##S## is the proof-system making part the formal system and ##\phi## is a wff (well formed formula) of the formal language. Note the blank on left of the turnstile symbol ##\vdash_S##, as far as I can tell it actually represents the empty set. So what does it mean ? I guess it actually means ##\phi## is a theorem of the formal system, i.e. there is a...
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