Write , where the are independent variables. Convolution gives the sum of two independent uniform variables:
Its plot is a triangle with vertices
For Test 1, the rejection probability is increasing in , so its size over is attained at and equals
Test 2 is also monotone under shifts in , so its size is . For , the triangular upper tail is
Equating this to gives
The power function of a statistical test for Test 1 is
Put . Test 2 rejects when
Using the two branches of the triangular distribution gives
Both functions equal at the least favourable null value .
The two tests have the same size, but their powers cross. At ,
At ,
Thus Test 2 is a same-size test that beats Test 1 at one alternative, while Test 1 beats Test 2 at another. By the crossing-power obstruction to a uniformly most powerful test,

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