In this chapter we consider independent random vectors Xi ∈ Rd for some d ≥ 1, assuming that they have a common distribution F0. It is no longer convenient to describe F0 by a cumulative distribution function, there being d dimensions along which to cumulate. Instead we describe distributions by the probabilities that they attach to sets. Thus F (A) means Pr(X ∈ A) for X ∼ F and A ⊆ Rd. We let δx denote the distribution under which X = x with probability 1. Thus δx(A) = 1x∈A.