This talk discusses several methods to compute confidence regions and confidence intervals for the true solution of a stochastic variational inequality, given the solution to a sample average approximation (SAA) problem. We justify these methods by establishing precise limit theorems, and present numerical results in applications including a statistical learning problem called the Lasso.