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Method and system for determining the effects of variation of N statistically distributed variables (N≧ 1) in a fabrication process for semiconductor and other electronic devices by constructing and using an N-variable model function G (x 1,..., x N) to model the process. A sequence of orthogonal polynomials is associated with each probability density function P i (x i) for each variable x i. These orthogonal polynomials, and products of these polynomials, are used to construct the model function G (x 1,..., x N), having undetermined coefficients. Coefficient values are estimated by results of measurements or simulations with variable input values determined by the zeroes (collocation points) of selected orthogonal polynomials. A Monte Carlo process is applied to estimate a probability density function associated with the process or device. Coefficients whose magnitudes are very small are used to identify regions of (x 1 …