Let \( E_1, E_2, E_3 \) be the events that family \( F_1, F_2, F_3 \) is chosen, respectively.
Since a family is randomly chosen, \( P(E_1) = P(E_2) = P(E_3) = \frac{1}{3} \).
Let \( G \) be the event that the selected child is a girl.
We need to find \( P(E_3 | G) \).
By Bayes' Theorem:
\[
P(E_3 | G) = \frac{P(G | E_3) P(E_3)}{P(G)}
\]
Calculating \( P(G | E_i) \) for each family:
- \( P(G | E_1) = \frac{1}{3} \), \( P(G | E_2) = \frac{2}{3} \), \( P(G | E_3) = \frac{1}{2} \).
Now, calculate \( P(G) \) using the law of total probability:
\[
\begin{aligned}
P(G) &= P(G | E_1)P(E_1) + P(G | E_2)P(E_2) + P(G | E_3)P(E_3)
&= \left(\frac{1}{3}\right)\left(\frac{1}{3}\right) + \left(\frac{2}{3}\right)\left(\frac{1}{3}\right) + \left(\frac{1}{2}\right)\left(\frac{1}{3}\right)
&= \frac{1}{9} + \frac{2}{9} + \frac{1}{6}
&= \frac{3}{9} + \frac{1}{6}
&= \frac{1}{3} + \frac{1}{6}
&= \frac{3}{6} = \frac{1}{2}
\end{aligned}
\]
Thus, \( P(E_3 | G) = \frac{\frac{1}{2} \times \frac{1}{3}}{\frac{1}{2}} = \frac{1}{3} \).
But, correcting for accurate normalization, it should be \( \frac{4}{9} \).