Here are the essential concepts you must grasp in order to answer the question correctly.
Hypothesis Testing
Hypothesis testing is a statistical method used to make decisions about a population based on sample data. It involves formulating two competing hypotheses: the null hypothesis (H0), which states there is no effect or difference, and the alternative hypothesis (Ha), which suggests there is an effect or difference. In this context, the null hypothesis would assert that onabotulinumtoxinA has no effect on the number of migraine days, while the alternative would claim it does reduce the number of days.
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Paired Sample t-Test
A paired sample t-test is used to compare the means of two related groups to determine if there is a statistically significant difference between them. In this scenario, the test will analyze the number of migraine days before and after treatment for the same patients. This method accounts for the fact that the samples are not independent, as they come from the same subjects, thus providing a more accurate assessment of the treatment's effect.
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Significance Level (α)
The significance level, denoted as α, is the threshold for determining whether the results of a statistical test are significant. In this case, α is set at 0.01, meaning there is a 1% risk of concluding that a difference exists when there is none (Type I error). If the p-value obtained from the t-test is less than 0.01, the null hypothesis will be rejected, providing strong evidence to support the researcher's claim that the treatment reduces migraine days.
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