## Unit 3 summary

### You should be able to

- Conduct a statistical hypothesis test of an observed result from an experiment that uses random assignment
- Write an appropriate null hypothesis for an experiment that uses random assignment
- Use Monte Carlo simulation in TinkerPlots™ to find the expected experimental variation from an experimental study, if the null hypothesis were true (randomization test)
- Calculate a p-value
- Formulate a conclusion

- Evaluate the
*internal validity* of a study using the following criteria:
- Temporal precedence
- Correlation of cause and effect
- No palusibel alternative explanations

### You should understand

- How to interpret the mean of a dummy variable
- How to interpret the difference in means between two groups
- The logic behind a randomization test, including:
- Why we take the observed outcomes as fixed
- Why we randomly reassign the observed outcomes to experimental groups
- Why we sample without replacement
- What the distribution of results represents

- What a p-value represents
- What internal validity means
- The role of random assignment in drawing cause-and-effect conclusions (internal validity)

### TinkerPlots™ skills

- Create a split dot plot
- Create a “shuffler” sampler
- Use the
`Ruler`

tool to find the difference in means
- Use the
`Reference line`

and `Divider`

tools to count the values in a distribution that are as or more extreme than a given value

### Vocab

- Categorical variable
- Numeric variable
- Dummy variable/Dummy coding
- Experiment
- Random assignment
- Experimental variation
- p-value
- Confounding variable
- Internal validity/cause-and-effect
- Probabilistically equivalent