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Statistical significance refers to the likelihood that a relationship observed in data is due to chance, usually determined through p-values. In contrast, practical significance considers whether the difference or relationship identified has real-world relevance or implications. A result can be statistically significant but not practically significant, meaning it might not be meaningful in a practical context. This distinction is crucial for researchers, as findings must be both statistically valid and practically applicable to inform decisions effectively.
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