Sampling-based methods for uncertainty and sensitivity analysis are reviewed. Topics considered include (I) separation of stochastic (i.e.,aleatory) and subjective (i.e., epistemic) uncertainty, (ii) construction of distributions to characterize subjective uncertainty, (iii) sampling procedures (i.e., random sampling, importance sampling, Latin hyper-cube sampling), (iv) analysis procedures (i.e., examination of scatterplots, regression analysis, stepwise regression analysis, correlation and partial correlation, rank transformations, identification of nonmonotonic and nonrandom patterns). Procedures are illustrated with (I) a model for two-phase fluid flow, (ii) a sequence of simple test functions, and (iii) a performance assessment for a radioactive waste disposal facility.