This article describes a generalized program for the computation of sampling errors. It employs computerized linearization of nonlinear estimates by the use of the first-order Taylor approximation. It can be used for any estimate derived from any “large” probability sample. In most instances the only inputs required are the weighted sample data and the form of the estimate whose precision is to be measured. In these cases, both the estimate and its sampling error can be produced with the same amount of data preparation and programming effort as is required to produce the estimate only.