Is the answer to this question wrong?
Consider the three alleles A, B, and O for the human blood types. Suppose that, in a certain population, the frequencies of these alleles are 0.45, 0.20, and 0.35, respectively. Kim and John, two members of the population, are married and have a son named Dan. Kim and Dan both have blood types AB. John’s blood type is B. What is the probability that John’s genotype is BB?
Answer: Clearly, John’s genotype is either BB or BO. Let E be the event that it is BB. Then $E^c$ is the event that John’s genotype is BO. Let F be the event that Dan’s genotype is AB. By Bayes’ formula, the probability we are interested in is
$$\begin{align}P(E|F)&=\frac{P(F|E)P(E)}{P(F|E)P(E)+P(F|E^c)P(E^c)}\\ &=\frac{(1/2)(0.2)^2}{(1/2)(0.2)^2+(1/4)(0.20)(0.35)}\\&=0.53\end{align}$$
Note that $P(E) = (0.20)^2$ and $P(E^c) = (0.20)(0.35)$ since for the two B alleles in John’s blood type, each is coming from one parent independently of the other parent. Remember John is the father.
My question: $E$ and $E^c$ are not even complements of each other!!
You are correct that events $E$ and $E^C$, as written, are not complements. However, given that we know John has type B blood, they are complements. So how do we reconcile that with the fact that their probabilities don't sum to $1$?
Let $B$ be the event that John has type $B$ blood. Then $P(E \cup E^C \mid B)=1$, in other words, $P(E\mid B) +P(E^C\mid B)=1$. We can update our Bayes calculation by conditioning everything on the event $B$ (which we assume has happened): \begin{align*} P(E \mid F ~\&~ B) &= \frac{P(F \mid E ~\&~ B)P(E \mid B)}{P(F \mid E ~\&~ B)P(E \mid B)+P(F \mid E^C ~\&~ B)P(E^C \mid B)}\\ &=\frac{P(F \mid E)P(E ~\&~ B)/P(B)}{P(F \mid E)P(E ~\&~ B)/P(B)+P(F \mid E^C ~\&~ B)P(E^C ~\&~ B)/P(B)}\\ &=\frac{P(F \mid E)P(E ) }{P(F \mid E)P(E )+P(F \mid E^C ~\&~ B )P(E^C~\&~ B)}\\ \end{align*} which is the expression calculated in the answer. (However, as noted, their calculation of $P(E^C ~\&~ B)$ should have an additional factor of $2$ to account for the fact that it doesn't matter which parent supplies the O allele and which supplies the B allele).
The steps that went into the simplification were:
If you're uncomfortable with the "conditional Bayes formula" that I wrote, then just remember that $P(\cdot \mid B)$ is a probability measure, so we could call it $\tilde{P}(\cdot)$. I.e., when I write $\tilde{P}(A)$ I mean $P(A \mid B)$. Then the conditional Bayes formula is: $$\tilde{P}(E\mid F) = \frac{\tilde{P}(F \mid E)\tilde{P}(E)}{\tilde{P}(F \mid E)\tilde{P}(E)+\tilde{P}(F \mid E^C)\tilde{P}(E^C )}.$$