In statistics, what does a p-value represent?

• A. The probability of obtaining the observed results (or more extreme) if the null hypothesis is true
• B. The probability that the null hypothesis is true
• C. The power of the statistical test
• D. The chance of committing a Type I error

Answer: (A)

The p-value measures how compatible your observed data are with the null hypothesis. Specifically, it is the probability, assuming the null is true, of obtaining a test statistic as extreme as the one you observed (or more extreme). A small p-value means the data look unlikely under the null, so you have evidence against it and may reject the null at your chosen significance level. However, the p-value is not the probability that the null is true, nor does it directly describe the test’s Type I error rate for this study or the test’s power.