Rejection of the null hypothesis occurs in statistical hypothesis testing when the evidence collected from a sample is strong enough to conclude that the null hypothesis is unlikely to be true. This typically involves comparing a test statistic to a critical value or assessing a p-value against a predetermined significance level (e.g., 0.05). If the evidence suggests that the observed effect is statistically significant, researchers reject the null hypothesis in favor of the alternative hypothesis. This decision implies that there is sufficient evidence to support a relationship or effect that the null hypothesis posits does not exist.
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