Past exam of the year 1 of the computer science course of the University of Oxford / 2022 / Discrete mathematics, continuous mathematics and probability resit / 9 / c

Write $Z=U^a$. Since $a>0$, the map is increasing on $[0,1]$, and for $0⩽z⩽1$,Differentiation givesand zero outside this interval. Since $B(1/a,1)=a$, this is exactly the beta distribution probability density function with parameters $(1/a,1)$. The power transform of a uniform random variable therefore satisfies $U^a\sim \mathrm{Beta}(1/a,1)$; the second parameter does not depend on $a$.

Let $W_i=U_i^2$. Applying the same measurable function separately to independent and identically distributed random variables preserves those two properties, andIn particular, these bounded random variables are integrable random variables. The weak law of large numbers givesIf $c>1/3$, then $\{{\overline{W}}_n>c\}\subseteq \{|{\overline{W}}_n-1/3|⩾c-1/3\}$, whose probability tends to zero. If $0⩽c<1/3$, then $\{{\overline{W}}_n⩽c\}\subseteq \{|{\overline{W}}_n-1/3|⩾1/3-c\}$, whose probability also tends to zero. Taking a complement in the second case provesThe positive gap from $1/3$ is essential to this argument. Convergence in probability alone does not determine the answer at the excluded threshold $c=1/3$.