Question

In a clinical trial of a drug intended to help people slop smoking, 132 subjects were treated with the drug for 13 wreks, and 10 subjects expecienced abdominal pain. If someone claims that more than 8% of the drug's users experience abdominal pain, that claim is supported with a hypothesis test conducted with a 0.05 significance level. Using 0.19 as an altemative value of p, the power of the test is 0.96. Intrrpret this value of the power of the test. The power of 0.96 shows that there is a % chance of rejecting the hypothesis of p= when the true proportion is actualy That is, it the proportion of users who experience abdominal pain is actually then there is a & chance of supporting the claim that the proportion of users who experience abdominal pain is than 0.08 (Type integers or decimals. Do not round.)

Answer 1

The power of the test is 0.96, meaning there is a 96% chance of rejecting the null hypothesis if the true proportion is 0.19.

Step-by-step explanation:

The power of a hypothesis test measures the probability of rejecting the null hypothesis when the alternative hypothesis is true. In this case, the alternative hypothesis states that more than 8% of the drug's users experience abdominal pain. The power of the test is given as 0.96, which means there is a 96% chance of rejecting the null hypothesis correctly when the true proportion of users who experience abdominal pain is actually 0.19. Put simply, if the proportion of users who experience abdominal pain is truly 0.19, there is a 96% chance of supporting the claim that the proportion is greater than 0.08.

Answer 2

The power of the test is 0.96, indicating a 96% chance of rejecting the null hypothesis when it is false.

Step-by-step explanation:

A hypothesis test is a statistical method used to assess the validity of a hypothesis about a population parameter. It involves collecting and analyzing data to determine whether observed results provide enough evidence to reject or fail to reject the null hypothesis, aiding in drawing conclusions from sample data about a larger population.

The power of a hypothesis test measures the probability of correctly rejecting the null hypothesis when it is false. In this case, the power of the test is 0.96, which means there is a 96% chance of rejecting the hypothesis that more than 8% of the drug's users experience abdominal pain, when the true proportion is actually 0.19. This indicates strong evidence in support of the claim that the proportion of users who experience abdominal pain is higher than 0.08.