## 3.10 Unit 3 summary

### 3.10.1 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

### 3.10.2 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)

### 3.10.3 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

### 3.10.4 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