Final answer:
To assess whether the majority of independents support a national health plan using the data, we apply hypothesis testing with a significance level of 0.05. If the p-value from the study is less than this alpha, we have strong evidence to support the claim, otherwise, the evidence is not sufficient.
Step-by-step explanation:
To determine whether data provides strong evidence to support a claim, such as the majority of independents supporting a national health plan, we use hypothesis testing. At a significance level of 0.05 (alpha = 0.05), we compare the p-value from the data against this threshold.
If the p-value is less than alpha, we reject the null hypothesis and conclude that there is sufficient evidence to support the claim. For example, if a p-value for a dataset is calculated to be 0.03, this would be less than the threshold of 0.05, leading to a rejection of the null hypothesis.
In contrast, if the p-value is greater than alpha, we do not reject the null hypothesis, suggesting that there is insufficient evidence to support the claim. For a dataset with a p-value of 0.1207 with alpha set at 0.05, we would not reject the null hypothesis as the evidence is not strong enough.
A test of independence, such as comparing poll responses to participants' ethnic groups, would also follow this procedure to determine if there is a relationship between the variables being tested.