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What is P-Value?

The p-value represents the likelihood that the disparity observed between two or more observed scores is a result of random chance. It is generated through statistical significance calculations. For a difference to be considered statistically significant, the p-value must be less than 0.05, indicating a low probability of the observed difference occurring by random variation alone.

Synonyms: Probability value

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Why is P-Value Important?

  • Statistical Significance Assessment: P-value serves as a crucial indicator in determining the statistical significance of observed differences between data points, helping researchers assess the validity and reliability of study findings.
  • Inference Confidence: A low p-value (typically less than 0.05) suggests that the observed disparity is unlikely to have occurred by random chance alone, providing researchers with confidence in drawing conclusions and making decisions based on the data.
  • Data Interpretation Guide: Understanding the significance of p-values guides researchers in interpreting study results, enabling them to discern meaningful differences from those that may arise due to random variation.

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