In hypothesis testing, which of the following is true?

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In hypothesis testing, the null hypothesis is assumed to be true until there is sufficient evidence to reject it in favor of the alternative hypothesis. It is not possible to reject the null hypothesis with 100% certainty, and there is always a chance of making a type I or type II error. P-values represent the probability of obtaining a test statistic as extreme or more extreme than the observed result, assuming that the null hypothesis is true. Finally, the null hypothesis and the research hypothesis are not necessarily the same thing. The null hypothesis usually represents no effect, while the research hypothesis represents a specific effect that the researcher is interested in testing.

In Hypothesis Testing, Which of the Following Is True