This simulator uses the Monte Carlo mathematical technique to predict outcomes by running multiple randomized simulations. Adjust parameters, set customizable ranges and weights, and analyze the most likely scenarios while understanding complex parameter interactions.
Input Parameters
Define the key variables for your simulation. Each parameter requires a name, a range (minimum and maximum values), and a weight (1-10) that determines its impact on the outcome. Higher weights indicate greater influence.
Parameter Name
Min Value
Max Value
Weight (1-10)
Simulation Settings
Choose the number of simulation iterations. More iterations increase accuracy but may require additional computation time. A good balance is 1,000 to 10,000 iterations, depending on the complexity of the model.
?More iterations provide more accurate results but may take longer to calculate.
Simulation Results
Once the simulation is complete, the results will be displayed below. The left panel provides detailed outcome probabilities, while the right panel visualizes probability distributions to help you interpret trends effectively.
Detailed Outcomes
No Results Yet
Set up your parameters and run a simulation to generate meaningful insights.
Calculating outcomes...
Probability Distribution
Visualization Ready
Execute a simulation to view the probability and likelihood of different outcomes.
Parameter Winners Analysis
Parameter Analysis Ready
Run the simulation to determine which parameters contribute most significantly to the final results.