Software cost estimation techniques predict the amount of effort required to develop a software system. Cost estimates are needed throughout the software lifecycle to determine feasibility of software projects and to provide for appropriate allocation or reallocation of available resources. As the cost of a project depends on the nature and characteristics of the project, the accuracy of the estimates depends on the amount of reliable information about the product to be developed. At the same time, most cost estimation models rely heavily on subjective expert evaluations affected by possibly high degree of imprecision and uncertainty. To assess the effect of imprecise evaluations, a comprehensive sensitivity analysis has been performed on a major cost estimation model, COCOMO II. Results of this analysis are described and explicated in this paper. To reduce risk of drawing biased conclusions, three different methods for sensitivity analysis have been employed: mathematical analysis of the estimating equation, Monte Carlo simulation, and error propagation. The results of the first two methods are very consistent and confirm expected highest sensitivity of the model to the imprecision of the size estimate. Error propagation allows determination of the combined impact of imprecision in multiple inputs and it is therefore most valuable from the practical point of view. The results obtained by this technique also indicate very strong sensitivity to the imprecision in size estimates. A possible way to cope with imprecise information in software cost estimation is indicated in the concluding part of the paper.