Felix Mercer examines why statistically significant results can be meaningless with large datasets. Using the MythBusters' yawn experiment and medical research examples, this episode reveals how massive samples detect trivial differences. Learn why effect size matters more than p-values for smarter decision-making.
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This content was created in partnership and with the help of Artificial Intelligence AI.
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