A priori power analysis is a statistical method used to determine the minimum sample size needed for a study to detect an effect of a given size with a certain level of confidence before data collection begins. This process helps researchers make informed decisions regarding their study design by estimating the power of the test, which reflects the probability of correctly rejecting the null hypothesis when it is false. By understanding the relationship between sample size, effect size, significance level, and power, researchers can optimize their study parameters to ensure robust results.
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