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To determine if the evidence suggests that a higher proportion of subjects in group 1 experienced drowsiness as a side effect than subjects in group 2 at the [tex]\(\alpha = 0.05\)[/tex] level of significance, we need to verify certain model requirements. We will examine each requirement one by one:
A. [tex]\(n_1 \hat{p}_1(1-\hat{p}_1) \geq 10\)[/tex] and [tex]\(n_2 \hat{p}_2(1-\hat{p}_2) \geq 10\)[/tex]:
- We need to check if the sample sizes and proportions meet the necessary condition for the normal approximation.
- This requirement is true.
B. The sample size is less than [tex]\(5 \%\)[/tex] of the population size for each sample:
- This means that the sample is a small fraction of the entire population.
- This requirement is true.
C. The samples are dependent:
- For the samples to be dependent, the selection or outcome in one group would have to affect the other.
- This requirement is false.
D. The samples are independent:
- If selecting or observing a subject in one group does not affect the selection or outcome in the other group, then the samples are independent.
- This requirement is true.
E. The sample size is more than [tex]\(5 \%\)[/tex] of the population size for each sample:
- This implies that the sample is a significant portion of the population, which can affect the assumption of independence and the sampling distribution.
- This requirement is false.
F. The data come from a population that is normally distributed:
- This model requirement pertains to the distribution of the population from which samples are taken.
- This requirement is false.
Given these considerations, the verified model requirements are:
- A. [tex]\(n_1 \hat{p}_1(1-\hat{p}_1) \geq 10\)[/tex] and [tex]\(n_2 \hat{p}_2(1-\hat{p}_2) \geq 10\)[/tex]
- B. The sample size is less than [tex]\(5 \%\)[/tex] of the population size for each sample.
- D. The samples are independent.
So, in summary, the model requirements that apply are:
- A. [tex]\(n_1 \hat{p}_1(1-\hat{p}_1) \geq 10\)[/tex] and [tex]\(n_2 \hat{p}_2(1-\hat{p}_2) \geq 10\)[/tex]
- B. The sample size is less than [tex]\(5 \%\)[/tex] of the population size for each sample.
- D. The samples are independent.
A. [tex]\(n_1 \hat{p}_1(1-\hat{p}_1) \geq 10\)[/tex] and [tex]\(n_2 \hat{p}_2(1-\hat{p}_2) \geq 10\)[/tex]:
- We need to check if the sample sizes and proportions meet the necessary condition for the normal approximation.
- This requirement is true.
B. The sample size is less than [tex]\(5 \%\)[/tex] of the population size for each sample:
- This means that the sample is a small fraction of the entire population.
- This requirement is true.
C. The samples are dependent:
- For the samples to be dependent, the selection or outcome in one group would have to affect the other.
- This requirement is false.
D. The samples are independent:
- If selecting or observing a subject in one group does not affect the selection or outcome in the other group, then the samples are independent.
- This requirement is true.
E. The sample size is more than [tex]\(5 \%\)[/tex] of the population size for each sample:
- This implies that the sample is a significant portion of the population, which can affect the assumption of independence and the sampling distribution.
- This requirement is false.
F. The data come from a population that is normally distributed:
- This model requirement pertains to the distribution of the population from which samples are taken.
- This requirement is false.
Given these considerations, the verified model requirements are:
- A. [tex]\(n_1 \hat{p}_1(1-\hat{p}_1) \geq 10\)[/tex] and [tex]\(n_2 \hat{p}_2(1-\hat{p}_2) \geq 10\)[/tex]
- B. The sample size is less than [tex]\(5 \%\)[/tex] of the population size for each sample.
- D. The samples are independent.
So, in summary, the model requirements that apply are:
- A. [tex]\(n_1 \hat{p}_1(1-\hat{p}_1) \geq 10\)[/tex] and [tex]\(n_2 \hat{p}_2(1-\hat{p}_2) \geq 10\)[/tex]
- B. The sample size is less than [tex]\(5 \%\)[/tex] of the population size for each sample.
- D. The samples are independent.
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