Okay, so I was asked this question in an interview on a machine learning expert position. To be honest, the question itself (and the hint by the interviewer) seemed quite ill-phrased, which probably is the reason I ended up failing the interview, and he thought I must be super dumb. Here is the original question.
You know your colleague has two kids, and also know one of them is a boy. What is the probability that the other one is a boy too?
I was a bit puzzled, then he gave me a hint, by asking me to use Bayes' theorem, which I knew from high school $$\mathbb{P}(A\cap B)=\mathbb{P}(A|B)*\mathbb{P}(B)$$ I could see that given one kid is a boy corresponds to event $B$, but could not really figure out the other quantities.
To confuse matters, he gave me hints like when you see people with two kids, most of the times it is a boy and a girl, right? I could not argue with him, obviously, but I cannot reach any such conclusion based on my personal observation either.
I tried to tell things like
- to calculate it we need empirical data like survey of all couples having two kids in the city/country etc.
- absent other information, the second child has the same probability of being a boy as the percentage of males in the country, assuming each kid's gender is independent
But seems she had some assumption about the scenario (that meant the problem can be solved purely mathematically) that I failed to clarify. Upon further thought, there may be some biological concepts on how chromosomes interact to decide the gender of the second kid (and whether it is biased one way or another), but that is hardly fair to expect from an ML engineer. Is that where the answer lies?
But the reason for this post is not to complain, but I am giving the context, just to ask what exactly am I missing in the question assuming it is meant to be a probability (and not biology) question.