Solution

ID: past-exam-of-the-simulation-and-statistical-programming-course-of-the-university-of-oxford/2023/2/a/i/solution

Write where , assigning zero elsewhere. The envelope ensures , and is nonnegative. Integrating its joint probability density over the auxiliary coordinate gives
Consequently . This proves normalization of a probability distribution; the change of integration order is justified by Tonelli's theorem.
The coordinates are generally dependent. For , their conditional probability density is
Thus has a uniform distribution on an interval whose endpoint depends on . They are independent exactly when is constant for -almost every , since only then do these conditional laws agree. In particular, is an exception: and are independent. An unconditional answer that they can never be independent would therefore be too strong.

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