The significance level, often denoted as α (alpha), is a threshold used in statistical hypothesis testing to determine whether to reject the null hypothesis. Commonly set at 0.05, it represents a 5% risk of concluding that a difference exists when there is none. This means that if the p-value obtained from a test is less than α, the results are considered statistically significant. In practical terms, the significance level helps researchers assess the strength of their findings. A lower significance level, such as 0.01, indicates a stricter criterion for significance, reducing the likelihood of false positives. Understanding this concept is crucial for interpreting results in fields like psychology, medicine, and social sciences.