I'm reading through this article (http://www.sciencedirect.com/science/article/pii/S0047259X06000662) where they have a population version of the Spearman rank correlation. I'm having a little bit of trouble understanding the author's derivation, which I reproduce as follows:
"For a two-dimensional random vector $X$ $=(X_{1},X_{2})'$ with distribution function $F$, univariate marginal distributions $F_{X_{1}}$, $F_{X_{2}}$ and a copula $C$ is defined by
$\rho_{S}=\frac{cov(F_{X_{1}}(X_{1}), F_{X_{2}}(X_{2}))}{\sqrt{var(F_{X_{1}}(X_{1}))}\sqrt{var(F_{X_{2}}(X_{2}))}}=$
$= \frac{cov(U_{1},U_{2})}{\sqrt{var(U_{1})}\sqrt{var(U_{2})}}=$
$=\frac{\int_{0}^{1}\int_{0}^{1}uv dC(u,v)-(\frac{1}{2})^{2}}{\sqrt{\frac{1}{12}}\sqrt{\frac{1}{12}}}=$
$=12\int_{0}^{1}\int_{0}^{1}C(u,v)dudv-3$
I understand every step with the exception of the last one. Where did the 3 come from? And why were they able to change the integrand from $uvdC(u,v)$ to $C(u,v)dudv$?
I'm trying to teach myself some basic copula theory so there are a few holes in my knowledge here and there.