Unit 1 summary
You should be able to
- 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
You should understand
- 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.,
- 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.
- Standard deviation