1.11 Unit 1 summary

Use Monte Carlo simulation to explore patterns in a random process:
- Model: Translate real life phenomena into a model to be used in the simulation process.
- Simulate: Use TinkerPlots™ to generate random outcomes from a model.
- Evaluate: Determine the “typical” result from a Monte Carlo model, and a range of likely results
Describe a distribution in terms of shape, center, and spread (using mean and SD as appropriate)
Calculate a range of likely values in a distribution using the mean and SD

That there is regularity in randomness
Why we need to run multiple simulated trials, and when you have run enough
What the mean represents in a distribution and why we use it to summarize the “typical” value in the distribution
What the standard deviation represents in a distribution and why we use it to summarize the variation in the distribution

Create a new sampler and use different devices to generate random outcomes (e.g., Spinner, Mixer, Counter).
Plot values from an attribute in a case table and organize (by separating) the the plotted values.
Numerically summarize the randomly generated outcomes from the trial (e.g., Count (N), Count (%)).
Automatically collect the results from many trials.
Find the mean and SD of a distribution
Use the Divider tool to select a range of values.