What does a p-value represent in research?

A p-value is a crucial concept in hypothesis testing within research. It quantifies the probability of obtaining results at least as extreme as the observed results, given that the null hypothesis is true. Essentially, it helps researchers determine whether to reject the null hypothesis. When the p-value is low (typically less than a significance level like 0.05), it suggests that the observed data would be highly unlikely if the null hypothesis were true, providing evidence against the null hypothesis.

This interpretation is fundamental for making informed conclusions in research studies. High p-values suggest insufficient evidence to reject the null hypothesis, while low p-values indicate a statistically significant result that may warrant further investigation or support for the alternative hypothesis. Understanding the p-value helps researchers assess the strength of their findings in the context of statistical significance.