Confounding Variables A pharmaceutical company has applied for approval to market a new arthritis medication. The research involved a test group that was given the medication and another test group that was given a placebo. Describe some possible confounding variables that could influence the results of the study.
Table of contents
- 1. Intro to Stats and Collecting Data55m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically1h 45m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables2h 33m
- 6. Normal Distribution and Continuous Random Variables1h 38m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 53m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 12m
- 9. Hypothesis Testing for One Sample2h 19m
- 10. Hypothesis Testing for Two Samples3h 22m
- 11. Correlation1h 6m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 20m
- 14. ANOVA1h 0m
10. Hypothesis Testing for Two Samples
Two Proportions
Problem 8.4.1
Textbook Question
What conditions are necessary to use the z-test for testing the difference between two population proportions?

1
Understand that the z-test for testing the difference between two population proportions is used to determine if there is a significant difference between the proportions of two populations.
Ensure that the data comes from two independent random samples. Independence is a key assumption for the z-test to be valid.
Verify that the sample sizes are sufficiently large. Specifically, for both populations, the expected counts of successes and failures should be at least 5. This means that for each sample, the conditions n₁p₁ ≥ 5, n₁(1-p₁) ≥ 5, n₂p₂ ≥ 5, and n₂(1-p₂) ≥ 5 must be satisfied, where n₁ and n₂ are the sample sizes, and p₁ and p₂ are the sample proportions.
Confirm that the sampling distribution of the difference between the sample proportions is approximately normal. This is typically ensured by the large sample size condition mentioned above.
Check that the populations are large enough relative to the sample sizes to satisfy the assumption of independence. Specifically, the population sizes should be at least 10 times larger than the sample sizes (N₁ ≥ 10n₁ and N₂ ≥ 10n₂).

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Z-Test
The z-test is a statistical method used to determine if there is a significant difference between the means of two groups or the proportions of two populations. It assumes that the sampling distribution of the sample proportion is approximately normal, which is valid under certain conditions, particularly when sample sizes are large enough.
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Normal Approximation
For the z-test to be applicable when comparing two population proportions, the sample sizes must be sufficiently large to ensure that the sampling distribution of the proportion is approximately normal. This is typically satisfied if both np and n(1-p) are greater than 5, where n is the sample size and p is the sample proportion.
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Independence of Samples
The samples being compared in a z-test for proportions must be independent of each other. This means that the selection of one sample does not influence the selection of the other, which is crucial for the validity of the test results and ensures that the observed differences are due to actual population differences rather than sampling bias.
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