## 2.9 Unit 2 summary

### 2.9.1 You should be able to

Conduct a statistical hypothesis test of an observed result, including:

• Write an appropriate null hypothesis that specifies a “no effect” probability model and a source of variation
• Use Monte Carlo simulation in TinkerPlots™ to simulate a study if the null hypothesis were true
• Model: Use a sampler to model the study if the null hypothesis were true
• Simulate: Run the simulation hundreds of times and collect the result of interest.
• Evaluate:
• Find a range of likely results if the null hypothesis were true
• Determine whether the observed result is compatible with the null hypothesis
• Formulate a conclusion

### 2.9.2 You should understand

The logic behind statistical hypothesis testing, including:

• The role of the null hypothesis as specifying a baseline to compare the observed result to
• Why we use Monte Carlo simulation
• What the distribution of results represents
• What we are checking for, in order to determine whether the observed result is compatible with the null model
• The sort of conclusions we can (and can’t) make from a statistical hypothesis test.

### 2.9.3 TinkerPlots™ skills

• Create a new sampler and use different devices to model a null hypothesis
• Plot values from a table and organize (by separating) the the plotted values.
• Numerically summarize values in a plot (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.

### 2.9.4 Vocab

• Null hypothesis
• “No effect” probability model