Our estimate of the true average μX is the sample mean ⟨Xm⟩ μXX≈Xm=1mnm∑α=1n∑k=1xα,k.
We can then use Eq. (9) σ2m=1mn2m∑α=1n∑kl=1(xα,k−⟨Xm⟩)(xα,l−⟨Xm⟩), and rewrite it as σ2m=σ2n+2mn2m∑α=1n∑k<l(xα,k−⟨Xm⟩)(xα,l−⟨Xm⟩), where the first term is the sample variance of all mn experiments divided by n and the last term is nothing but the covariance which arises when k≠l.