What does a p-value indicate in hypothesis testing?

What does a p-value indicate in hypothesis testing?

• A. The probability that the null hypothesis is true.
• B. The probability of observing data as extreme as or more extreme than observed if the null is true.
• C. The probability of making a Type I error.
• D. The probability of replicating the study with the same results.

Answer: (B)

A p-value measures how compatible the observed data are with the assumption that there is no effect. It is the probability, assuming the null hypothesis is true, of obtaining data as extreme as or more extreme than what was actually observed. It is not the probability that the null is true, nor the probability of making a Type I error, nor the likelihood of replicating the study. A small p-value indicates the observed pattern would be unlikely if the null were true, so you would reject the null at your chosen significance level. A large p-value suggests the data are reasonably consistent with the null, so you would not reject it. The specific threshold you use (like 0.05) is a decision rule you set in advance. Remember that the p-value doesn’t tell you the size of the effect or the probability of reproducing the result in a new study. It’s about data under the assumption of the null and is influenced by sample size and variability.

A p-value measures how compatible the observed data are with the assumption that there is no effect. It is the probability, assuming the null hypothesis is true, of obtaining data as extreme as or more extreme than what was actually observed. It is not the probability that the null is true, nor the probability of making a Type I error, nor the likelihood of replicating the study.

A small p-value indicates the observed pattern would be unlikely if the null were true, so you would reject the null at your chosen significance level. A large p-value suggests the data are reasonably consistent with the null, so you would not reject it. The specific threshold you use (like 0.05) is a decision rule you set in advance.

Remember that the p-value doesn’t tell you the size of the effect or the probability of reproducing the result in a new study. It’s about data under the assumption of the null and is influenced by sample size and variability.