# Steps to do a Monte Carlo simulation

I'm trying to do a Monte Carlo simulation but I'm lost in the process. The big question I want to answer is what's the probability I have to do a certain amount of work. In my solution I've already prepared my experiment and got my set of observations, 100 to be more specific (100 values that describe my capacity of work). After that, I've ordered my results in ascending form, calculated the mean, median, mode, and standard deviation, but from this point forward I'm lost.

I've read some articles and they mention the concept of poisson distribution but I don't understand how to use it or how it comes into play.

Another good question is whats the number of simulations I should do to get a more probable result.

What am I missing? What's the set of steps I should follow to do a Monte Carlo simulation? Can you give me a set of steps or suggest me the documentation I could follow to accomplish what I want? Thank your for yuor time and al the help!

Do you understand how Monte Carlo simulation works?

Just start simulating...

Set $$M = 0$$ (number of successes).

Now... you have to do many iterations, say $$N = 10000$$ iterations.

At each iteration you generate some random input B,
you perform a computation on B to check if certain event A has occurred.

If A has occurred you add $$1$$ to $$M$$.

Repeat this process many many times $$N$$.

Finally compute the ratio $$M/N$$, this is your result,
i.e. your approximation for $$P(A)$$.

In most simplistic terms, this is all you have to do.

It is just simulation so there is nothing so complicated there.

A basic example can be found on Wikipedia. Did you check it?

• Hi Peter thanks for your answer, I will check the wikipedia article May 2, 2020 at 10:15