Paper 3, Section II, 25K

Probability and Measure
Part II, 2011

(i) State and prove Kolmogorov's zero-one law.

(ii) Let (E,E,μ)(E, \mathcal{E}, \mu) be a finite measure space and suppose that (Bn)n1\left(B_{n}\right)_{n \geqslant 1} is a sequence of events such that Bn+1BnB_{n+1} \subset B_{n} for all n1n \geqslant 1. Show carefully that μ(Bn)μ(B)\mu\left(B_{n}\right) \rightarrow \mu(B), where B=n=1BnB=\cap_{n=1}^{\infty} B_{n}.

(iii) Let (Xi)i1\left(X_{i}\right)_{i \geqslant 1} be a sequence of independent and identically distributed random variables such that E(X12)=σ2<\mathbb{E}\left(X_{1}^{2}\right)=\sigma^{2}<\infty and E(X1)=0\mathbb{E}\left(X_{1}\right)=0. Let K>0K>0 and consider the event AnA_{n} defined by

An={SnnK}, where Sn=i=1nXiA_{n}=\left\{\frac{S_{n}}{\sqrt{n}} \geqslant K\right\}, \quad \text { where } \quad S_{n}=\sum_{i=1}^{n} X_{i}

Prove that there exists c>0c>0 such that for all nn large enough, P(An)c\mathbb{P}\left(A_{n}\right) \geqslant c. Any result used in the proof must be stated clearly.

(iv) Prove using the results above that AnA_{n} occurs infinitely often, almost surely. Deduce that

lim supnSnn=\limsup _{n \rightarrow \infty} \frac{S_{n}}{\sqrt{n}}=\infty

almost surely.