ABSTRACT
The Monte Carlo method is one of the most universally used approximate numerical techniques, especially where stochastic effects are important, though it has also been used to examine deterministic problems. The Monte Carlo analysis technique is particularly suited to accommodate the intrinsically variable nature of the properties of foods and other bio-products and uncertainties in the manufacturing processes they undergo. The term Monte Carlo is used to describe any approach to a problem where a probabilistic analogue to a given mathematical problem is setup and solved by stochastic sampling. The advantages of the Monte Carlo method are that it is conceptually easy to understand and robust in operation. The Monte Carlo method allows use of standard nonparametric statistical tests concerning confidence intervals. The engine of the Monte Carlo method is some procedure to generate random numbers. The numerical output from any Monte Carlo simulation can be assembled in frequency histogram form.
