Rejecting the null refers to the decision made in hypothesis testing when there is sufficient statistical evidence to conclude that the null hypothesis is not true. This action suggests that the observed data deviates significantly from what the null hypothesis predicts, leading to support for the alternative hypothesis. When researchers reject the null, they indicate that their findings are unlikely to have occurred by random chance alone, which often implies that a real effect or difference exists.
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