{"id":218381,"date":"2025-01-26T08:00:03","date_gmt":"2025-01-26T08:00:03","guid":{"rendered":"https:\/\/namso-gen.co\/blog\/when-p-value-is-less-than-0-01\/"},"modified":"2025-01-26T08:00:03","modified_gmt":"2025-01-26T08:00:03","slug":"when-p-value-is-less-than-0-01","status":"publish","type":"post","link":"https:\/\/namso-gen.co\/blog\/when-p-value-is-less-than-0-01\/","title":{"rendered":"When p-value is less than 0.01."},"content":{"rendered":"

Title: The Significance of a p-value Less Than 0.01 in Statistical Analysis<\/p>\n

Introduction:
\nIn the realm of statistical analysis, the p-value plays a crucial role in determining the significance of a research finding. A p-value less than 0.01 implies strong evidence against the null hypothesis, suggesting that the observed effect is not due to chance. Let us delve into the significance of this threshold and understand its implications.<\/p>\n

**When the p-value is less than 0.01, it indicates a highly significant result.**
\nA p-value of less than 0.01 means that there is less than a 1% chance that the observed result occurred purely due to random chance or sampling error. Such a low p-value provides strong evidence against the null hypothesis, giving researchers confidence in the statistical significance of their findings.<\/p>\n

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