It is 1935 in Cambridge, and a woman at a garden party claims she can taste whether the milk or the tea was poured into the cup first — a boast that becomes the founding parable of experimental testing. You present eight cups, four each way, in random order, and she must sort them. Work out, before she tastes a drop, how surprising a perfect or near-perfect score would be under the hypothesis that she is merely guessing, by enumerating the possible arrangements directly rather than leaning on any large-sample formula. Get it wrong and you credit a lucky guesser with a gift, or design a test too weak to reveal a real one — the whole logic of significance is built, cup by cup, on this exact enumeration.
Allen, the first woman to win the Turing Award, made her foundational contributions to compiler optimization theory at IBM from the 1950s through the 1970s, developing techniques for analyzing and transforming program control flow to generate efficient machine code. This is deep and important computer science, but it belongs entirely to the domain of programming language implementation and systems software, with no connection to statistical hypothesis testing, probability theory, or experimental design. Nothing in Allen's body of work addresses how to compute exact probabilities under a combinatorial null hypothesis or how to structure a randomized experiment like the tea-tasting test. Her expertise, while historically significant, simply does not intersect with the mathematical and statistical content this problem is built around.
Wasserman, known for 'All of Statistics' and for building bridges between classical statistics and machine learning from the 1990s onward, has broad expository command of exact and asymptotic inference alike, including nonparametric hypothesis testing, and would readily recognize the tea-tasting problem as a textbook example of exact combinatorial inference; his writing does cover Fisher's exact test as a standard topic. But his own distinctive research contributions lie in nonparametric function estimation, minimax theory, and topological data analysis rather than in originating or extending exact permutation-testing methodology itself. He functions more as a rigorous synthesizer and teacher of this material than as a historical contributor to it, which places him solidly in the middle of this batch rather than among the top carriers.
Battle #123 · 8/10/2026, 11:38:58 AM · this result is deterministic: the same two personas on this problem always resolve the same way.