What does the p-value tell you and what does it not tell you?

• A. It indicates the magnitude of the difference between groups.
• B. It indicates the probability that the observed difference could occur by chance if the null is true.
• C. It determines the clinical significance.
• D. It directly measures the study's power.

Answer: (B)

The p-value shows how compatible the observed difference is with the assumption of no real difference. Specifically, it is the probability, under the null hypothesis, of obtaining a result as extreme or more extreme than what was actually observed. This is why it’s the best choice: it directly describes what would be expected by chance if there were no true effect.

It does not tell you how large the difference is—that’s the role of the effect size. It does not indicate whether the difference is clinically important. It does not measure the study’s power or the probability that the null is true; it depends on sample size and data variability and only speaks to compatibility with the null under repeated sampling.