If the p-value is less than or equal to 0.05, what should you do?

When the p-value is less than or equal to 0.05, it indicates strong evidence against the null hypothesis in statistical hypothesis testing. This threshold is commonly used in many scientific disciplines to determine whether the results observed in the data are statistically significant.

Rejecting the null hypothesis suggests that the findings are unlikely to have occurred by random chance alone, leading to the conclusion that there is a statistically significant difference or effect present in the data being analyzed. This conclusion typically supports the alternative hypothesis, indicating that the research findings merit further consideration or exploration.

In contrast, options suggesting rerunning the test or increasing the sample size imply that the initial results were somehow inconclusive, which is not the case when the p-value clearly indicates significance. Accepting the null hypothesis would contradict the evidence provided by the p-value, which demonstrates that there is likely a genuine effect or difference present in the data. Thus, based on the given information, the appropriate action is to reject the null hypothesis and acknowledge the statistically significant finding.