XLSTAT gives a choice of more than 20 distributions to describe the uncertainty of the values that a variable can take. Simulation models are used in many areas such as finance and insurance, medicine, oil and gas prospecting, accounting, or sales prediction.įour elements are involved in the construction of a simulation model:ĭistributions are associated with random variables. XLSTAT-Sim allows you to define the distributions, and then obtain through simulations an empirical distribution of the input and output variables as well as the corresponding statistics. If some "result" variables depend of these "distributed" variables by the way of known or assumed formulae, then the "result" variables will also have a distribution. Simulation models allow us to obtain information, such as mean or median, on variables that do not have an exact value, but for which we can know, assume or compute a distribution. Before running the model, you need to create the model, defining a series of input and output (or result) variables. Monte Carlo Simulation is a module that allows building and computing simulation models, an innovative method for estimating variables, whose exact value is not known, but that can be estimated by means of repeated simulation of random variables that follow certain theoretical laws. ![]() ![]() What is a Monte Carlo Simulation in XLSTAT?
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