In hypothesis testing, what does a p-value less than 0.05 typically indicate?

Explanation: A p-value less than 0.05 signifies that the probability of observing the test statistic, or something more extreme, under the null hypothesis is less than 5%. This threshold, commonly used in hypothesis testing, indicates strong evidence against the null hypothesis, prompting its rejection in favor of the alternative hypothesis. It is a measure of the strength of evidence, not absolute proof. This approach underpins statistical decision-making across fields, providing a rigorous standard for hypothesis evaluation. Option A: A p-value does not prove the null hypothesis; it measures evidence against it. Option B: Sample size affects power, but p-value interpretation does not inherently reflect sample size issues. Option D: Confidence intervals are separate from p-values and serve to estimate population parameters. Option E: A p-value below 0.05 typically indicates sufficient evidence to reject the null hypothesis.