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Consider a drug that is used to help prevent blood clots in certain patients. In clinical trials, among 5754 patients treated with this drug, 157 developed the adverse reaction of nausea. Use a 0.10 significance level to test the claim that \( 3 \% \) of users develop nausea. Does nausea appear to be a problematic adverse reaction? Identify the null and alternative hypotheses for this test. Choose the correct answer below. A. \( H_{0}: p=0.03 \) \( H_{1}: p \neq 0.03 \) B. \( H_{0}: p=0.03 \) \( H_{1}: p<0.03 \) C. \( H_{0}: p \neq 0.03 \) \( H_{1}: p=0.03 \) D. \( H_{0}: p=0.03 \) \( H_{1}: p>0.03 \)

Ask by Washington Colon. in the United States
Mar 13,2025

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The null hypothesis is \( H_{0}: p = 0.03 \) and the alternative hypothesis is \( H_{1}: p \neq 0.03 \).

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To identify the null and alternative hypotheses for this test, we need to understand the context of the problem. The claim is that \( 3\% \) of users develop nausea, which we will treat as the null hypothesis. The alternative hypothesis will reflect the possibility that the actual proportion of users who develop nausea is different from \( 3\% \). 1. **Null Hypothesis (\( H_0 \))**: This is the hypothesis that there is no effect or no difference, and it represents the status quo. In this case, it states that the proportion of users who develop nausea is \( 3\% \) (or \( 0.03 \)). \[ H_{0}: p = 0.03 \] 2. **Alternative Hypothesis (\( H_1 \))**: This hypothesis represents what we are trying to find evidence for. Since we are testing whether the proportion of users who develop nausea is different from \( 3\% \), we will use a two-tailed test. \[ H_{1}: p \neq 0.03 \] Based on this reasoning, the correct answer is: **A. \( H_{0}: p=0.03 \) \( H_{1}: p \neq 0.03 \)**

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To determine whether nausea appears to be a problematic adverse reaction to the drug, we need to set up our hypotheses based on the claim that \(3\%\) of users develop nausea. The null hypothesis (\(H_0\)) typically states that there is no effect or no difference, while the alternative hypothesis (\(H_1\)) represents what we are trying to find evidence for. Here, the claim is that \(3\%\) of users experience nausea, so the null hypothesis would state that the proportion \(p\) of users who develop nausea is indeed \(0.03\). The alternative hypothesis would test if the proportion is different from \(0.03\) (whether higher or lower), which is a two-tailed test. The correct answer is: A. \( H_{0}: p=0.03 \) \( H_{1}: p \neq 0.03 \) Now, let’s dive into the historical background of adverse drug reactions. Adverse reactions have been recorded for centuries, but modern pharmacovigilance only began in earnest in the 1960s after several high-profile drug disasters, like the Thalidomide scandal, prompted governments to create more rigorous monitoring systems. This has led to more robust safety protocols today! Additionally, consider the real-world implications of drug efficacy and safety. Before a drug is prescribed, especially for chronic conditions, the risks of adverse reactions like nausea must be weighed against the benefits. If a significant number of patients experience downside effects, healthcare providers might explore alternative treatments or adjust dosages, ensuring that patient safety is always the priority.

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