๐Ÿงฎ Brain Teaser

The Flippant Juror: Three Jurors and a Coin

A three-person jury must decide the guilt or innocence of a defendant. Two jurors are competent: each independently makes the correct decision with probability p>12p > \frac{1}{2}. The third juror is completely useless โ€” she decides by flipping a fair coin (probability 12\frac{1}{2} of being correct).

The jury uses majority rule: the defendant is convicted if and only if at least 2 of the 3 jurors vote "guilty."

Compare the probability that the jury reaches the correct verdict under majority rule to the probability that a single competent juror reaches the correct decision. Which is larger?

The answer may surprise you.

majority rulejury paradoxindependenceconditional probabilityelegant cancellation

Answer: The Flippant Juror: Three Jurors and a Coin

Key Idea / Intuition

Your first instinct might be: adding a random coin-flipper to the jury should hurt performance โ€” she's completely uninformative! But remarkably, the majority-of-three rule (with two competent jurors and one random one) gives exactly the same probability of a correct verdict as a single competent juror alone. The coin-flipper is perfectly harmless under majority rule. The reason: the flippant juror only changes the outcome when the two competent jurors already disagree โ€” and in that case, a fair coin is exactly as good as a third competent voter would be, in the sense that the overall probability works out to the same number.


Formal Proof / Solution

Setup. Let pp be the probability each competent juror is correct. Let jurors be J1J_1 (competent), J2J_2 (competent), J3J_3 (coin flipper, correct with probability 12\frac{1}{2}). All decisions are independent.

Single competent juror. The probability of a correct verdict is simply pp.

Jury majority rule. The jury is correct if at least 2 of the 3 are correct. Let's compute P(correct)P(\text{correct}).

Condition on the two competent jurors:

| J1J_1 correct | J2J_2 correct | Probability | Jury correct iff... | |---|---|---|---| | Yes | Yes | p2p^2 | Always (2 already correct) | | Yes | No | p(1โˆ’p)p(1-p) | J3J_3 correct (prob 12\frac{1}{2}) | | No | Yes | (1โˆ’p)p(1-p)p | J3J_3 correct (prob 12\frac{1}{2}) | | No | No | (1โˆ’p)2(1-p)^2 | Never (at most 1 correct) |

So:

P(juryย correct)=p2โ‹…1+p(1โˆ’p)โ‹…12+(1โˆ’p)pโ‹…12+(1โˆ’p)2โ‹…0P(\text{jury correct}) = p^2 \cdot 1 + p(1-p) \cdot \frac{1}{2} + (1-p)p \cdot \frac{1}{2} + (1-p)^2 \cdot 0

=p2+2p(1โˆ’p)โ‹…12= p^2 + 2p(1-p) \cdot \frac{1}{2}

=p2+p(1โˆ’p)= p^2 + p(1-p)

=p2+pโˆ’p2= p^2 + p - p^2

=p.= p.

Conclusion. The jury of three (two competent, one coin-flipper) under majority rule has exactly the same probability pp of reaching the correct verdict as a single competent juror. The useless juror contributes nothing โ€” but she also takes nothing away.

Why this is beautiful. The key insight is that the flippant juror only gets a "casting vote" when the two competent jurors disagree, which happens with probability 2p(1โˆ’p)2p(1-p). In that tie-breaking role, her fair coin contributes 12\frac{1}{2}, giving the term 2p(1โˆ’p)โ‹…12=p(1โˆ’p)2p(1-p) \cdot \frac{1}{2} = p(1-p). And p2+p(1โˆ’p)=pp^2 + p(1-p) = p โ€” it telescopes perfectly. The useless juror is perfectly neutral, not harmful.

This also shows: replacing a competent juror with a coin-flipper doesn't hurt majority rule! The "loss" from downgrading one juror is exactly compensated by the majority structure.

Source: Fifty Challenging Problems in Probability with Solutions, Frederick Mosteller, Problem 10

Type: ProbabilitySource: Fifty Challenging Problems in Probability with Solutions, Frederick Mosteller, Problem 10Edit on GitHub โ†—