Question

As we've previously seen, equations describing situations often contain uncertain parameters, that is, parameters that aren't necessarily a single value but instead are associated with a probability distribution function. When more than one of the variables is unknown, the outcome is difficult to visualize. A common way to overcome this difficulty is to simulate the scenario many times and count the number of times different ranges of outcomes occur. popular simulation is called a Monte Carlo Simulation. In this problem-solving exercise you will develop a program that will perform a Monte Carlo simulation on a simple profit function. One such Consider the following total profit function: Where Pris the total profit, n is the number of vehicles sold and Pv is the profit per vehicle. PART A Compute 5 iterations of a Monte Carlo simulation given the following information: n follows a uniform distribution with minimum of 1 and maximum 10 Pv follows a normal distribution with a mean of $4500 and a standard deviation of $1000 Number of bins: 10 Recall that for all practical purposes we will use 3 std. deviations from the mean as the maximum value for parameters following a normal distribution Obviously, 5 iterations are not very many In fact, typically you would simulate 10,000 iterations or so to view meaningful results but I figured that I'd give you a break ®. If you'd like to compute 10,000 iterations by hand for extra credit, go ahead. i.)What are the ranges for the 10 bins? ii.) Fill in the table below: Parameter Iteration 1 Iteration 2 Iteration 3 Iteration 4 Iteration 5 $3000 $4500 $2100 $6500 Bin # ii.) Fill in the of occurrences of each bin 10

Answer 1

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