The p value plays a crucial role in hypothesis testing and helps researchers make decisions about their data. For instance, a low p value (typically less than 0.05) suggests that the observed effect is statistically significant, meaning it is unlikely to have occurred by chance alone. This enables epidemiologists to reject the null hypothesis and consider alternative hypotheses.
