I am confused about a conditional probability question from One Thousand Exercises in Probability by Geoffery Grimmett & David Stirzaker:
A man possesses five coins, two of which are double-headed, one is double-tailed, and two are normal. He shuts his eyes, picks a coin at random, and tosses it. What is the probability that the lower face of the coin is a head?
He opens his eyes and sees that the coin is showing heads; what is the probability that the lower face is a head?
He shuts his eyes again, and tosses the coin again. What is the probability that the lower face is a head?
I'm ok with the first two questions. For the third question, I think he asks for the probability that the lower face is a head on the second toss given the upper face is a head on the first toss. Let $D_H$ be the event that the coin is double-headed, $D_T$ the event that the coin is double-tailed, $N$ the event the coin is normal, $H_i$ the event the lower face is head on the $i$th toss, and finally $U_i$ the event the upper face is head on the $i$th toss.
Now we need to find $\mathbb{P}(H_2 \mid U_1)$. However, what we know from the second question is $$\mathbb{P}(D_H \mid U_1)= \frac{2}{3}, \quad \mathbb{P}(D_T \mid U_1) =0, \quad \mathbb{P}(N\mid U_1)=\frac{1}{3},$$
and I failed to deduce what $\mathbb{P}(H_2 \mid U_1) = \frac{\mathbb{P}(H_2 \; \cap\; U_1)}{\mathbb{P}(U_1)}$ is from what we know.
The underlying assumption is that given the choice of coin, the two tosses are independent. We will formalize this information.
So let $C\in \{hh,ht,tt\}$ be the choice of coin with probabilities $2/5,2/5$ and $1/5$, respectively. Let $U_i, L_i\in\{h,t\}$ be the upper and lower face in the $i$'th toss. Let $A=\{U_1=h\}$ be the event that we get an upper head in the first toss and $B=\{L_2=h\}$ a lower head in the second. We get by a standard application of Bayes that $P(C=hh|A) = 2/3$ and $P(CC=ht|A)=1/3$.
Now, the conditional independence means that $$P(A\cap B|C)=P(A|C)\; P(B|C)$$ which you may rewrite in the following way: $$ P(B\cap C|A) = P(B|C)\; P(C|A) $$ Then $$P(B|A) = \sum_C P(B\cap C|A) = \sum_C P(B|C)\; P(C|A) = 1\times \frac23 + \frac12 \times \frac13 + 0\times 0 = \frac56.$$