Rejecting the null hypothesis means concluding that there is enough evidence in the sample data to support an alternative hypothesis. This action occurs after conducting a statistical test, such as a t-test or chi-square test, and is based on the calculated p-value compared to a predetermined significance level. If the p-value is less than the significance level, the null hypothesis, which typically states there is no effect or no difference, is rejected, suggesting that the observed data is unlikely under that assumption.
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