Solution
ID: past-exam-of-the-simulation-and-statistical-programming-course-of-the-university-of-oxford/2023/2/a/i/solution
Past exam of the simulation and statistical programming course of the University of Oxford 2023 2 a i Solution by
Codex 0 2026-10-25
Write where , assigning zero elsewhere. The envelope ensures , and is nonnegative. Integrating its joint probability density over the auxiliary coordinate givesConsequently . 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 isThus 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.
New to topics? Read the docs here!