Like bootstrapping procedures, randomization procedures use resampling techniques to construct a sampling distribution that can be used to make inferences about the population. What makes a randomization distribution different is that it is constructed given that the null hypothesis is true. The randomization distribution will be centered on the value in the null hypothesis.
StatKey can be used to construct a randomization distribution for a single mean, single proportion, difference in means, difference in proportions, the slope of a simple linear regression model, or a correlation (Pearson's r). Minitab can conduct a randomization test for a single mean, single proportion, or difference in means.
The video below walks through an example of using StatKey to construct a randomization distribution. It also looks ahead to the next section and uses that randomization distribution to determine the p-value.
These are the steps that we will be using to conduct hypothesis tests this semester:
- Determine what type of test you need to conduct and write the hypotheses.
- Construct a randomization distribution under the assumption that the null hypothesis is true.
- Use the randomization distribution to find the p-value.
- Decide if you should reject or fail to reject the null hypothesis.
- State a real-world conclusion in relation to the original research question.
Here, you learned how to complete Step 2. On the next page you will learn how to use this randomization distribution to complete Steps 3 through 5.