A certain drug is used to treat asthma. In a clinical trial of the drug, 30 of 296 treated subjects experienced headaches (based on data from the manufacturer). The accompanying calculator display shows results from a test of the claim that less than 12% of treated subjects experienced headaches. Use the normal distribution as an approximation to the binomial distribution and assume a 0.01 significance level to complete parts (a) through (e) below. 1-PropZTest prop <0.12 z--0.987327567 p= 0.1617410403 p=0.1013513514 n= 296 a. Is the test two-tailed, left-tailed, or right-tailed? O Left-tailed test Two-tailed test

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**Title: Statistical Analysis of Asthma Drug Clinical Trial**

**Introduction:**
In a clinical trial of a drug used to treat asthma, 30 out of 296 treated subjects experienced headaches. The drug manufacturer claims that less than 12% of treated subjects experience headaches. Using the normal distribution as an approximation to the binomial distribution, and assuming a 0.01 significance level, we will explore the hypothesis testing process.

**Questions and Explanation:**

**a. Tail Type Test:**
- Determine if the test is two-tailed, left-tailed, or right-tailed.
  - Options:
    - Left-tailed test
    - Two-tailed test
    - Right-tailed test

**b. Test Statistic:**
- Calculate the z-score.
  - "Round to two decimal places as needed."

**c. P-value:**
- Determine the P-value.
  - "Round to four decimal places as needed."

**d. Null Hypothesis:**
- Identify and evaluate the null hypothesis: \( H_0: p = 0.12 \), \( p > 0.12 \), \( p \neq 0.12 \), \( p < 0.12 \).
- Decide whether to reject the null hypothesis:
  - Options include:
    - Reject due to P-value greater than significance level.
    - Reject due to P-value less than/equal to significance level.
    - Fail to reject due to P-value greater than significance level.
    - Fail to reject due to P-value less than/equal to significance level.

**e. Final Conclusion:**
- Based on the analysis, conclude if the manufacturer's claim holds true.

**Graph/Diagram:**
- The diagram included displays a 1-PropZTest result.
  - Key values:
    - \( \text{prop} < 0.12 \)
    - \( z = -0.987327567 \)
    - \( p = 0.1617140403 \)
    - \( \hat{p} = 0.1013513514 \)
    - \( n = 296 \)

**Summary:**
This exercise involves understanding hypothesis testing in a real-world context, focusing on determining if evidence supports the manufacturer’s claim about the drug’s side effects.
Transcribed Image Text:**Title: Statistical Analysis of Asthma Drug Clinical Trial** **Introduction:** In a clinical trial of a drug used to treat asthma, 30 out of 296 treated subjects experienced headaches. The drug manufacturer claims that less than 12% of treated subjects experience headaches. Using the normal distribution as an approximation to the binomial distribution, and assuming a 0.01 significance level, we will explore the hypothesis testing process. **Questions and Explanation:** **a. Tail Type Test:** - Determine if the test is two-tailed, left-tailed, or right-tailed. - Options: - Left-tailed test - Two-tailed test - Right-tailed test **b. Test Statistic:** - Calculate the z-score. - "Round to two decimal places as needed." **c. P-value:** - Determine the P-value. - "Round to four decimal places as needed." **d. Null Hypothesis:** - Identify and evaluate the null hypothesis: \( H_0: p = 0.12 \), \( p > 0.12 \), \( p \neq 0.12 \), \( p < 0.12 \). - Decide whether to reject the null hypothesis: - Options include: - Reject due to P-value greater than significance level. - Reject due to P-value less than/equal to significance level. - Fail to reject due to P-value greater than significance level. - Fail to reject due to P-value less than/equal to significance level. **e. Final Conclusion:** - Based on the analysis, conclude if the manufacturer's claim holds true. **Graph/Diagram:** - The diagram included displays a 1-PropZTest result. - Key values: - \( \text{prop} < 0.12 \) - \( z = -0.987327567 \) - \( p = 0.1617140403 \) - \( \hat{p} = 0.1013513514 \) - \( n = 296 \) **Summary:** This exercise involves understanding hypothesis testing in a real-world context, focusing on determining if evidence supports the manufacturer’s claim about the drug’s side effects.
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