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? B. \( H_{0}: p=0.03 \) \( H_{1}: p<0.03 \) C. \( H_{0}: p \neq 0.03 \) \( H_{1}: p=0.03 \) D. \( H_{0}: p=0.03 \) \( H_{1}: p>0.03 \) 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.)
Solución de inteligencia artificial de Upstudy
Responder
Solución

¡Inicia sesión para desbloquear respuestas gratis!
Una plataforma de aprendizaje en la que confían millones de estudiantes y profesores reales.

Respondido por UpStudy AI y revisado por un tutor profesional
Beyond the Answer
To interpret the results of your study, let’s dive into the real-world application of hypothesis testing. Understanding how to test claims like the one about the drug helps inform healthcare decisions, ensuring patients are well-informed about potential risks. In practice, a high incidence of adverse effects like nausea—if proven significant—could lead to changes in prescribing guidelines or even drug withdrawal from the market. When performing these tests, many can trip over common mistakes. For instance, using the wrong null and alternative hypotheses can skew results. In this case, make sure you differentiate between testing for an increase, decrease, or simply a difference in proportions. Confirming the assumptions behind your chosen statistical test also helps avoid incorrect conclusions—always check sample size and proportion before proceeding!
