A priori power analysis is a statistical method used to determine the necessary sample size for a study, aiming to achieve a desired level of statistical power before data collection begins. This type of analysis helps researchers estimate how large their sample should be to reliably detect an effect if one exists, thereby preventing underpowered studies that may yield inconclusive results. It plays a vital role in experimental design by guiding decisions on sample sizes based on expected effect sizes, significance levels, and the desired power of the test.
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