Paper 1, Section II, 26 K26 \mathrm{~K}

Probability and Measure
Part II, 2013

State Dynkin's π\pi-system /d/ d-system lemma.

Let μ\mu and ν\nu be probability measures on a measurable space (E,E)(E, \mathcal{E}). Let A\mathcal{A} be a π\pi-system on EE generating E\mathcal{E}. Suppose that μ(A)=ν(A)\mu(A)=\nu(A) for all AAA \in \mathcal{A}. Show that μ=ν\mu=\nu.

What does it mean to say that a sequence of random variables is independent?

Let (Xn:nN)\left(X_{n}: n \in \mathbb{N}\right) be a sequence of independent random variables, all uniformly distributed on [0,1][0,1]. Let YY be another random variable, independent of (Xn:nN)\left(X_{n}: n \in \mathbb{N}\right). Define random variables ZnZ_{n} in [0,1][0,1] by Zn=(Xn+Y)mod1Z_{n}=\left(X_{n}+Y\right) \bmod 1. What is the distribution of Z1Z_{1} ? Justify your answer.

Show that the sequence of random variables (Zn:nN)\left(Z_{n}: n \in \mathbb{N}\right) is independent.