Risk simulation has become a standard alternative to the utilization of single estimates for input data to investment appraisal models. Under the risk simulation approach managers define probability distributions for relevant input factors. During this process management may consciously or subconsciously assume certain relationships between the input variables. These interdependencies are often omitted from the models, however, under the justification that they are accounted for implicitly in the values attributed to the variables by management. It is demonstrated in this paper that such omissions may lead to significant errors in the observed distributions of the selected appraisal criteria. Various forms of discriminate sampling are introduced and an example is cited for which certain discriminate schemes are shown to be more accurate than traditional independent sampling.