Conditional Probability: Conceptual Doubts Cleared (8)

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Question

A family has 2 children. Given that at least one is a boy, what is the probability that both are boys? (Assume boys and girls are equally likely.)

Solution — Step by Step

For two children, the equally likely outcomes are: BB, BG, GB, GG (where order matters: first child, second child).

Each has probability 1/4.

“At least one is a boy” rules out GG. The reduced sample space is {BB, BG, GB}, three equally likely outcomes.

P(BBat least one boy)=P(BB and at least one boy)P(at least one boy)P(BB \mid \text{at least one boy}) = \frac{P(BB \text{ and at least one boy})}{P(\text{at least one boy})}

Numerator: P(BB)=1/4P(BB) = 1/4.

Denominator: P(at least one boy)=3/4P(\text{at least one boy}) = 3/4.

P=1/43/4=13P = \frac{1/4}{3/4} = \frac{1}{3}

Final answer: P=13P = \dfrac{1}{3}

Why This Works

Conditioning shrinks the sample space. Once we know at least one child is a boy, GG is impossible — we should only count outcomes consistent with the given information.

The non-intuitive answer (1/3, not 1/2) trips up most students. The instinct is “the other child is independent, so 1/2”. But the conditioning event isn’t “the first is a boy” — it’s “at least one is a boy”, which includes BG and GB. The asymmetry produces 1/3.

Alternative Method

Think of it as P(AB)/P(B)P(A \cap B)/P(B) directly:

  • AA = “both boys”, BB = “at least one boy”
  • AB=AA \cap B = A (because BB satisfies both), so P(AB)=P(BB)=1/4P(A \cap B) = P(BB) = 1/4
  • P(B)=1P(GG)=3/4P(B) = 1 - P(GG) = 3/4
  • P(AB)=(1/4)/(3/4)=1/3P(A|B) = (1/4)/(3/4) = 1/3

Common Mistake

The classic wrong answer: “We know one is a boy, so the other is independent → 1/2”. This implicitly conditions on a specific child being a boy (e.g., “the older is a boy”), which is a different event. Conditioning on “at least one” includes the BG and GB cases, not just one of them.

If the question said “the elder child is a boy”, the answer would be 1/2.

Always write out the sample space when in doubt about conditional probability. The mechanical method (count favourable / count conditioning) never lies.

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