What do small p-values suggest regarding the null hypothesis?

Small p-values suggest that the observed data is unlikely to have occurred under the assumption that the null hypothesis is true. When a p-value is low, it indicates strong evidence against the null hypothesis, leading researchers to consider rejecting it in favor of an alternative hypothesis. This statistical significance helps researchers conclude that there is enough evidence to suggest an effect or difference exists.

In the context of hypothesis testing, a small p-value typically signifies that the results observed in the data are statistically significant, implying that the observed distribution of data points is not just due to random chance, hence supporting the argument against the null hypothesis. Researchers generally use a predefined significance level (like 0.05), and if the p-value falls below this threshold, it reinforces the decision to reject the null hypothesis.