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? \[ \begin{array}{l}H_{0}: p=0.03 \\ H_{1}: p \neq 0.03 \\ H_{0}: p=0.03 \\ H_{1}: p<0.03 \\ H_{0}: p \neq 0.03 \\ H_{1}: p=0.03\end{array} \] \( H_{0}: p=0.03 \) \( H_{1}: p>0.03 \) Identify the test statistic for this hypothesis test. The test statistic for this hypothesis test is -1.21. (Round to two decimal places as needed.) Identify the \( P \)-value for this hypothesis test. The P-value for this hypothesis test is \( \square \). (Round to three decimal places as needed.)

A bit of historical context: The use of anticoagulants to prevent blood clots dates back to the early 20th century, with the development of warfarin. This medication was first used as a rat poison before its life-saving potential for humans was realized. Today, we have a range of anticoagulants, but monitoring their side effects, like nausea, remains crucial for patient safety! Now, for real-world application: In clinical settings, it's essential to regularly evaluate medications for their side effects. When a significant number of patients experience nausea, healthcare providers might reconsider the risk-benefit ratio of the drug for specific patient populations or explore alternative therapies to enhance patient comfort while managing the risk of clots. Regular monitoring and trials help ensure we keep improving patient outcomes!