Let $A, B \text{ and } C$ be events in a sample space while $A$ and $B$ are disjoint events. We know $P(A) = 2P(B)$, $P(C|A) = \frac{2}{7}$, $P(C|B) = \frac{4}{7}$. What is the result of $P(C | (A \cup B))$?
I was trying to expand the $P(C | (A \cup B))$ and plug in $P(A)$ and $P(B)$ to find the probability. But I found that this is not a good way to approach this problem.
What was the problem you found while expanding? It seems straightforward
$$ P(C | A \cup B) = \frac{P(C\cap (A \cup B)}{P(A \cup B)} = \frac{P((C \cap A)\cup (C \cap B))}{P(A)+P(B)} \stackrel{*}{=} \frac{\frac 47 P(B) + \frac47 P(B)}{3P(B)} = \frac{8}{21} $$
Note that is this situation you have that:
$P(A \cup B) = P(A)+P(B)-P(A \cap B) = P(A)+P(B)$
Since $A$ and $B$ are disjoint, $C\cap A$ and $C\cap B$ are also disjoint and so $P((C\cap A) \cup (C\cap B)) = P(C\cap A)+P(C \cap B)$
$P(C \cap A)= P(C|A) P(A) = \frac 27 P(A) = \frac 47 P(B)$
$P(C\cap B) = P(C|B) P(B) = \frac 47 P(B)$