Past exam of the mathematics course of the University of Cambridge 2016 iii Paper 210 2 c Solution Created 2026-10-03 Updated 2026-10-06
Put and . Use the quadratic scan statistic and reject when . Under the null hypothesis, each has the chi-squared distribution with degrees of freedom. The chi-squared concentration inequality gives , by the union bound. Since , the proposed Type I error is at most .
For the true set , has the same chi-squared distribution. We need a lower-tail bound that remains positive even when is close to one. Set . The chi-squared Chernoff lower-tail bound gives : indeed for . To verify this last inequality, its derivative is ; the expression in parentheses is strictly concave, starts at zero, and changes sign once, so the minimum occurs at an endpoint, where the inequality holds.
The function is convex with , so on this interval. Consequently implies . Failure to reject then requires , giving Type II error at most , uniformly in . An explicit, deliberately conservative answer isThe sharp constant is unnecessary; the detection scale is .