p-value

statistics

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July 23, 2026

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In statistics, a p-value represents the probability of obtaining observed results, or more extreme results, if the null hypothesis is true. The null hypothesis is a statement of no effect or no difference.123

A low p-value (typically less than 0.05) suggests that the observed data is unlikely to have occurred by random chance alone, leading to the rejection of the null hypothesis and the conclusion that the result is statistically significant. Conversely, a high p-value indicates that the observed results are likely due to random variation, and the null hypothesis cannot be rejected. Statistical significance does not imply the importance or practical impact of a finding, only that it is unlikely to be due to chance.23

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statistics
Hypothesis testing
A concept known as the p-value provides a convenient basis for drawing conclusions in hypothesis-testing applications. The p-value is a measure of how likely the sample results are, assuming the null hypothesis is true; the smaller the p-value, the less likely the sample results. If the p-value is less than…
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A concept known as the p-value provides a convenient basis for drawing conclusions in hypothesis-testing applications. The p-value is a measure of how likely the sample results are, assuming the null hypothesis is true; the smaller the p-value, the less likely the sample results. If the p-value is less than…
Read More