What does a p-value represent in psychological data?

• A. The probability that the null hypothesis is true.
• B. The probability, under the null, of observing data as extreme as observed.
• C. The probability that the alternative hypothesis is true.
• D. The effect size of the observed difference.

Answer: (B)

The p-value tells you how surprising the observed data would be if there were no real effect. It is the probability, under the assumption that the null hypothesis is true, of obtaining data as extreme as what was observed (or more extreme). In practice, a small p-value means your result is unlikely under the null and provides evidence against it (often leading to rejection at a chosen significance level). A large p-value means the data aren’t unusual under the null, so you don’t have evidence to reject it.

Keep in mind what the p-value does and does not convey: it is not the probability that the null hypothesis is true, nor the probability that the alternative is true, and it does not measure the size or practical importance of an effect. It also depends on the sample size and the specific test used (one-tailed vs two-tailed).