Which statement is true about the p value as described?

Which statement is true about the p value as described?

• A. A p value is the probability of the null being true.
• B. A p value is the probability of observing the data under the alternative hypothesis.
• C. A p value is the probability value.
• D. A p value is the probability of Type I error.

Answer: (C)

The p value reflects how compatible your observed data are with the null hypothesis when the null is assumed true. It is the probability, under that assumption, of obtaining results as extreme as (or more extreme than) what you actually observed. That makes it a probability value—the probability of the observed (or more extreme) data assuming the null is true. It is not the probability that the null hypothesis is true, nor the probability of the alternative, and it isn’t the Type I error rate itself (that rate is set by your alpha level and relates to long-run decisions, not the single p value). A small p value means the data are unlikely under the null, helping you decide whether to reject the null at your chosen significance level.

The p value reflects how compatible your observed data are with the null hypothesis when the null is assumed true. It is the probability, under that assumption, of obtaining results as extreme as (or more extreme than) what you actually observed. That makes it a probability value—the probability of the observed (or more extreme) data assuming the null is true. It is not the probability that the null hypothesis is true, nor the probability of the alternative, and it isn’t the Type I error rate itself (that rate is set by your alpha level and relates to long-run decisions, not the single p value). A small p value means the data are unlikely under the null, helping you decide whether to reject the null at your chosen significance level.