This question: 1 point(s) possible Submit quiz Suppose 246 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 thi $20 \%$ of users develop nausea. Identify the null and alternative hypotheses for this test. Choose the correct answer below. A. \[ \begin{array}{l} H_{0}: p=0.20 \\ H_{1}: p>0.20 \end{array} \] B. \[ \begin{array}{l} H_{0}: p=0.20 \\ H_{1}: p \neq 0.20 \end{array} \] c. \[ \begin{array}{l} H_{0}: p=0.20 \\ H_{1}: p<0.20 \end{array} \] D. \[ \begin{array}{l} H_{0}: p>0.20 \\ H_{1}: p=0.20 \end{array} \] Identify the test statistic for this hypothesis test. The test statistic for this hypothesis test is $\square$. (Round to two decimal places as needed.) Identify the P-value for this hypothesis test. The P-value for this hypothesis test is $\square$. (Rnuind in three rlarimal nlares ae nearlert)

Step 1 ：Identify the null and alternative hypotheses for this test. The null hypothesis is usually a statement of no effect or no difference. The alternative hypothesis is what you might believe to be true or hope to prove true. In this case, we are testing the claim that more than 20% of users develop nausea. So, the null hypothesis should be that the proportion of users who develop nausea is 20%, and the alternative hypothesis should be that the proportion is more than 20%. The null and alternative hypotheses for this test are: \[ \boxed{ \begin{array}{l} H_{0}: p=0.20 \ H_{1}: p>0.20 \end{array} } \]

Step 2 ：Calculate the test statistic for this hypothesis test. The test statistic can be calculated using the formula for a one-sample z-test for proportions, which is \((p_{hat} - p_0) / \sqrt{(p_0 * (1 - p_0)) / n}\), where \(p_{hat}\) is the sample proportion, \(p_0\) is the hypothesized population proportion, and \(n\) is the sample size. The test statistic for this hypothesis test is approximately \(\boxed{0.77}\) (rounded to two decimal places).

Step 3 ：Calculate the P-value for this hypothesis test. The P-value can be calculated by finding the probability that a z-score is greater than the calculated test statistic, since this is a one-tailed test. The P-value for this hypothesis test is approximately \(\boxed{0.222}\) (rounded to three decimal places).