MHB Is Marginalization Always Valid for Joint Probabilities?

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The discussion centers on proving the equation $$P(B \land C) = P(B \land C | A) P(A) + P(B \land C | \lnot A) P( \lnot A)$$ using principles from set theory and probability. It is established that since events A and not A are mutually exclusive, the sum rule applies, leading to the conclusion that the probabilities can be separated into their respective conditional probabilities. The proof utilizes the general product rule to confirm that the equation holds true regardless of the value of $$P(A)$$. Thus, the relationship between joint probabilities and conditional probabilities is validated. This confirms that marginalization in this context is always valid.
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Given $$P(B \land C)$$ will it always be true that $$P(B \land C | A) P(A) + P(B \land C | \lnot A) P( \lnot A)$$ (regardless what $P(A)$ would be)?

How can I prove this?
 
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tmt said:
Given $$P(B \land C)$$ will it always be true that $$P(B \land C | A) P(A) + P(B \land C | \lnot A) P( \lnot A)$$ (regardless what $P(A)$ would be)?

How can I prove this?

Hi tmt, (Smile)

We have from set theory:
$$P(B \land C) = P(B \land C \land (A \lor \lnot A))
= P((B \land C \land A) \lor (B \land C \land \lnot A))
$$
Since $A$ and $\lnot A$ are mutually exclusive, as are subsets of them, it follows from the sum rule that:
$$P((B \land C \land A) \lor (B \land C \land \lnot A)) = P(B \land C \land A) + P(B \land C \land \lnot A)
$$
Then, from the general product rule, it follows that:
$$ P(B \land C \land A) + P(B \land C \land \lnot A) = P(B \land C \mid A)P(A) + P(B \land C \mid \lnot A)P(\lnot A)
$$
So indeed, without knowing anything about $P(A)$, we can state that:
$$P(B \land C) = P(B \land C \mid A)P(A) + P(B \land C \mid \lnot A)P(\lnot A)$$
 
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