ABSTRACT
Monte Carlo (MC) methods [1,2] can be viewed in the present context as providing a means for computationally simulating the stochastic nature of errors and their influences on experimental and calculated results. An MC simulation involves generating random values for variables (x i ) of interest, over and over many times, and calculating a result for each set of variables.
