Power analysis assesses sample size to achieve significant p-values in research, highlighting necessary effect sizes.
When designing a study, you need to justify the sample size you aim to collect. If one of your goals is to observe a p -values lower than the alpha level you decided upon (e.g., 0.05), one justification for the sample size can be a power analysis. A power analysis tells you the probability of observing a statistically significant effect, based on a specific sample size, alpha level, and true effect size.
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Daniël Lakens (2017) studied this question.
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