In significance testing, a p-value below the chosen alpha indicates:

• A. The null hypothesis is true.
• B. The data were collected improperly.
• C. The alternative hypothesis is true.
• D. The data are unlikely under the null hypothesis.

Answer: (D)

When the p-value is smaller than the chosen alpha, it means the observed result is unlikely if the null hypothesis is true. The p-value is the probability, under the assumption that the null is true, of obtaining data as extreme or more extreme than what was observed. If this probability is below alpha, you reject the null at that significance level, concluding the data provide evidence against the null. It doesn’t prove the alternative hypothesis is true, only that the data are not well explained by the null. The other options misinterpret what a small p-value says: it does not show the null is true, imply improper data collection, or guarantee that the alternative is true.