Quantile proof of the Glivenko-Cantelli theorem

For a cumulative distribution function $G$, let $Q(u)=\inf \{x:G(x)\ge u\}$, $0<u<1$. Right continuity gives $Q(u)\le x$ exactly when $u\le G(x)$, including at atoms. Thus applying $Q$ to independent uniform variables $U_i$ constructs an independent sample with distribution function $G$. Its empirical distribution function is $G_n(x)=F_n(G(x))$, where $F_n$ is the uniform-sample empirical distribution function. Consequently ${\sup }_x|G_n(x)-G(x)|\le {\sup }_{t\in [0,1]}|F_n(t)-t|$. For the uniform sample, monotonicity and a grid of mesh $1/m$ bound the last supremum by the largest error at grid points plus $1/m$. The strong law of large numbers on the countable union of all such grids proves the almost-sure limit. This construction proves the theorem for distributions with atoms as well as continuous distributions.