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To determine whether the proportion of people within each treatment group who experienced dizziness is the same, you would use the **Test for Homogeneity**. This test is appropriate when comparing the distribution of a categorical variable (in this case, dizziness) across different groups (the medications).

In this case, you are testing whether the proportion of dizziness differs across the five different treatments (Tordol, Placebo, Naproxen, Tylenol, Advil). A **Chi-Square Test for Homogeneity** helps assess whether the proportions are consistent across these groups.

Would you like further explanation on this or details about how the test works?

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Here are five related questions:
1. What is the difference between a Chi-Square Test for Homogeneity and a Test for Independence?
2. How do you calculate the Chi-Square statistic for homogeneity?
3. What assumptions must be met to use the Test for Homogeneity?
4. What are the steps for performing a Chi-Square test in a statistical software?
5. Can the test results indicate which specific medication causes more dizziness?

**Tip:** Always ensure that the expected frequencies in each category are sufficiently large (usually 5 or more) to meet the assumptions of the Chi-Square test.

What type of test would you use to determine if the proportion of people within each treatment group who experienced dizziness are the same?

Explore how to use the Chi-Square Test for Homogeneity to determine if the proportion of dizziness differs across different pain medications. Analyze the data from a research study comparing medications like Tordol, Placebo, and others to see if they produce different dizziness rates.

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