Web Reference: Aug 11, 2025 · The p-value in statistics measures how strongly the data contradicts the null hypothesis. A smaller p-value means the results are less consistent with the null and may support the alternative hypothesis. Common cutoffs for statistical significance are 0.05 and 0.01. The p -value is widely used in statistical hypothesis testing, specifically in null hypothesis significance testing. In this method, before conducting the study, one first chooses a model (the null hypothesis) and the alpha level α (most commonly 0.05). Sep 4, 2025 · p-values are a statistical tool for testing whether data align with the assumption of no true effect under the null hypothesis. A small p-value suggests the results are unlikely if the null hypothesis is correct.
YouTube Excerpt: We shouldn't accept the conclusions of let's say a study before also thinking about whether or not the findings are
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