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SimulAr: Monte Carlo Simulation in Excel
At the left of the window distribution types are placed. By selecting each distribution a
fitting process is done and the graph will be updated showing the cumulative probabilities of the
historical data histogram and the cumulative probabilities of the fitted distribution. A perfect fit
indicate a 45º straight line between this relationship, that means, the cumulative probabilities are the
same indicating that SimulAr has been found a distribution that exactly fit the data series. To
examine which it is the distribution that best fit the historical data you should observe the
comparative graph for each distribution function and choose the one most nearly resemble to the
perfect fit (blue line). Nevertheless, it is always advisable to use a fairness approach when using this
feature because your data cannot be representative or some other factors like outliers can affect the
fitness process. In those cases, the distribution that best fit your data will lack of practical sense.
The theoretical distribution determined and their respective function written according to
SimulAr is located in the upper right corner of the window. For example, for the sales data
presented before, a normal distribution with mean 10,710.8567 and standard deviation of 5,266.204
produce a quite good fitness and you could consider it as reasonable when selecting these
parameters as input variable when modeling the product sales. However, choosing other
distributions you can find that logistic distribution fit better than normal distribution:
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