1 / 11

# Monte Carlo Simulation - PowerPoint PPT Presentation

Monte Carlo Simulation. Presented by Megan Aldrich and Tiffany Timm. What is Monte Carlo?. Uses random numbers to generate a simulation to mimic real data Helps find statistics for data that is really messy Use of a computer is required. Discovery and First Use.

Related searches for Monte Carlo Simulation

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.

## PowerPoint Slideshow about 'Monte Carlo Simulation' - americus

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

### Monte Carlo Simulation

Presented by Megan Aldrich and Tiffany Timm

• Uses random numbers to generate a simulation to mimic real data

• Helps find statistics for data that is really messy

• Use of a computer is required

• First used by Enrico Fermi in 1930s for neutron diffusion

• Documented by John von Neumann in the 1940’s during the Manhattan Project of World War II

• Popular because gambling was a rising sport and was coined the name Monte Carlo by Neumann’s partner Stainslaw Ulam who loved poker

• Easy to use

• Can make the complex data simple

• Does not take a lot of time to analyze

• Inexpensive

• Original expense to develop and operate simulations can be high

• Not sufficient in dealing with small numbers and usually has the operator estimating when this happens

• List all possible outcomes for each event.

• Determine the probability of each outcome.

• Determine subsets of the integers which have the same relative frequencies as the probabilities.

• Set up a correspondence between the outcomes and the subsets.

• Select a random number.

• Using each random number to represent the corresponding event, perform the experiment and note the outcome.

• Repeat until desired confidence.

As the owner of a small grocery store you have a choice of hiring:

• Two cashiers who do their own bagging, and each of whom can check out a shopper in two minutes, or

• One cashier and one bagboy who, working as a team, can check out a shopper in one minute.

We want to find the best scenario.

Based on our experience for every one minute:

• Zero people get in line 30% of the time

• One person gets in line 40% of the time

• Two people get in line 30% of the time

Using this system we can find the expected wait time per customer and the expected line length they will encounter.

• We generated random numbers in Excel and used a program written by Tiffany to run the experiment

• We want to explore:

Ho: Mx = My

H1: Mx > My

• We reject the null hypothesis in favor of the alternative hypothesis. This shows that the average wait time for a one-lane system is longer than a two-lane system.

• Therefore, we would choose a two-lane system to effectively lower the wait time for customers.

• Under what circumstances would you use the Monte Carlo Simulation?

• Name three ways you can generate random numbers.