Suppose 227 subjects are treated with a drug that is used to treat pain and 54 of them developed nausea. Use a 0.10 significance level to test the claim that more than \( 20 \% \) of users develop nausea. Identify the null and alternative hypotheses for this test. Choose the correct answer below. A. \( H_{0}: p=0.20 \) \( H_{1}: p>0.20 \) B. \( H_{0}: p>0.20 \) \( H_{1}: p=0.20 \) C. \( H_{0}: p=0.20 \) \( H_{1}: p<0.20 \) D. \( H_{0}: p=0.20 \) \( H_{1}: p \neq 0.20 \)

To test the claim that more than 20% of users develop nausea, we start with our null and alternative hypotheses. The null hypothesis typically represents the status quo or the statement we are testing against, while the alternative hypothesis represents the claim we are interested in verifying. In this case, we want to see if the proportion of users who develop nausea is greater than 20%. Therefore, the correct pair of hypotheses is: A. \( H_{0}: p=0.20 \) \( H_{1}: p>0.20 \) This indicates that we are assuming initially that the proportion of nausea is 20% and testing if it is significantly greater than that. Moreover, it’s interesting to note that hypothesis testing is a powerful tool used not just in clinical trials but in various fields, from psychology to market research, helping us make informed decisions based on data-driven evidence!