Monte Carol simulation is a practical tool used in determining
contingency and can facilitate more effective management of cost estimate
uncertainties. Given the right Monte Carlo simulation tools and skills, any
size project can take advantage of the advancements of information availability
and technology to yield powerful results.
Monte Carlo sampling refers to the traditional technique for using random
or pseudo-random numbers to sample from a probability distribution. The term
Monte Carlo was introduced during World
War II as
a code name for simulation of problems associated with development of the
atomic bomb. Today, Monte Carlo techniques are applied to a wide variety of
complex problems involving random
behavior.
A wide variety of algorithms are available for generating random samples from
different types of probability distributions.
Monte
Carlo sampling techniques are entirely random — that is, any given sample may
fall anywhere within the range of the input distribution. Samples, of course, are
more likely to be drawn in areas
of the
distribution which have higher probabilities of occurrence. In the cumulative
distribution shown earlier, each Monte Carlo sample uses a new random number
between 0 and 1. With enough iterations,
Monte
Carlo sampling "recreates" the input distributions through sampling.
A problem of clustering, however, arises when a small number of iterations are
performed
In PMI-RMP Exam Expect to See between 4-7 questions that ask you to
interpret the Monte Carlo simulation diagram, see the below example;
As you see, the diagram above shows histogram and a cumulative
distribution, in Exam, Expect that you will be asked for example to find P-45
or P50, it is simply means probability of 50% for achieving a specific cost, which
as illustrated from the cumulative distribution above
equal to 74,753,000$
Also expect to find questions such as, if the owner has a budget of the
project equal to 60,000 $ and he wants to have a confidence level of
50%, what is the contingency reserve that the project manager needs to
allocate to achieve this confidence level? the answer is the difference
between 60,000 and 74,753,00 $
the characteristics of Monte-Carlo simulation is also a big
topic in the exam and you have to understand them well
Note that the above diagram was for a cumulative distribution given, you
have to distinguish with the same histogram but with a Normal distribution
given as the below diagram
Here the summation of the vertical bars starting from the left side will
give the cumulative distribution as shown on the table at the right side
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