This article concerns setting standard errors and confidence intervals for the parameters of an unknown distribution when the data is subject to right censoring. The bootstrap, which is an elaboration of the jackknife, provides a general method for answering such questions. The validity of bootstrap methods is investigated using real data, computer simulations, and, in the final section, brief theoretical considerations.