Statistical significance refers to the likelihood that an observed effect or association is not due to random chance. It indicates that the results obtained are unlikely to have occurred purely by accident (Sharma, 2021). A p-value measures the magnitude of an observed phenomenon. It could be the correlation between two variables, the mean difference between groups, or the risk of a specific event. A common statistical measure that quantifies the evidence against the null hypothesis. A low p-value (typically < 0.05) suggests statistical significance. On the other hand, clinical significance also known as practical significance, assigns importance to a result based on its genuine and quantifiable effects in a clinical context. It involves a number needed to treat (NNT) which is an effect size that measures the average number of patients who need to be treated to prevent one additional adverse outcome or to benefit one patient over the control group (Sharma, 2021). Both statistical and clinical significance are crucial in advancing evidence-based practice. Researchers use statistical significance to determine whether an intervention or treatment has an effect beyond what would be expected by chance. However, statistical significance alone does not guarantee practical relevance or meaningful impact in real-world scenarios (Sharma, 2021). On the other hand, Evidence-based practice projects use clinically significant findings to guide treatment decisions, improve patient outcomes, and inform guidelines. Clinically significant findings are reproducible to a higher degree than those merely statistically significant. In practice, clinicians consider whether an observed effect is meaningful for patient care. For instance, if a drug reduces heart attacks by 1% (statistically significant), but the NNT is 100, it may not be clinically significant. Conversely, a 10% reduction in heart attacks (clinically significant) with an NNT of 10 would be more impactful. While statistical significance validates the reliability of study results, clinical significance assesses their impact on real-world practice. Both aspects are crucial for evidence-based decision-making, ensuring that research findings translate into meaningful benefits for patients and healthcare systems (Sharma, 2021)