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Monte Carlo Simulation Tutorial

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Monte Carlo Simulation
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This tutorial shows how to use Microsoft Excel to develop Monte Carlo simulations without the use of add-ins or special software.

The possibilities are limitless, of course, so no tutorial will exhaust the topic.  However, the information presented here provides a solid fundamental understanding of the core concepts, and some advanced techniques for modeling more complex problems.

After completing the tutorial you should have a sufficient understanding of Monte Carlo concepts and Excel capabilities to begin building your own Monte Carlo simulations applied to a wide range of business problems.

You may also download Excel workbooks containing all the major examples presented here, in return for a small donation.

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Currently, the design of various systems and complexes is quite expensive, time-consuming and time-consuming process. The only way to assess their functioning, and also to save both on time of design time and costs, necessary for their realization, is computer simulation. In addition, simulation at the design stage facilitates the synthesis and analysis of signal processing algorithms, the implementation of which involves the use of digital computing devices.

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One of the types of modeling is simulation modeling - a method of research in which the system under study is repla ced by a model that describes the real system in order to obtain information about it. When simulating systems, random variables or processes with different laws of probability distribution.

As you may know, the Monte Carlo model is a group of numerical methods for studying random processes. The essence of the method is that the process is described by a mathematical model using a random variables generator, the model is repeatedly computed, and the probability characteristics of the process in question are calculated based on the data obtained.

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