What does interpretation of quantitative results often require?

Interpreting quantitative results often necessitates understanding effect sizes, as they provide essential information about the magnitude and practical significance of relationships or differences observed in a study. Effect sizes quantify the strength and direction of a phenomenon, allowing researchers and practitioners to gauge whether the findings have meaningful implications beyond mere statistical significance. This is crucial in evidence-based practice, as it helps clinicians and decision-makers determine the relevance of the results to real-world situations and inform their application in various contexts, such as healthcare interventions or policy decisions.

While descriptive statistics summarize data, generalizability addresses how well findings can apply to broader populations, and qualitative narratives provide detailed contextual understanding, it is the effect size that directly aids in the interpretation of quantitative data, revealing how impactful the findings are in a practical sense. This aspect is vital when assessing the effectiveness of different interventions or understanding the scale of associations, making it the key component of quantitative result interpretation.