In regression analysis, the p-value helps determine the significance of the relationship between an independent variable and the dependent variable. Simply put, it tells you how likely it is that the observed results are due to chance rather than a real effect. A low p-value (typically less than 0.05) suggests that there is strong evidence against the null hypothesis, indicating that the independent variable has a significant impact on the dependent variable. Conversely, a high p-value suggests that any observed effect may be due to random variation, meaning the independent variable may not significantly influence the dependent variable.