## 1.11 Unit 1 summary

### 1.11.1 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

### 1.11.2 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

### 1.11.3 TinkerPlots™ skills

• 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.

### 1.11.4 Vocab

• Model
• Trial
• Result
• Distribution
• Mean
• Standard deviation