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Sample size estimation is crucial in research, ensuring studies are adequately powered to detect true effects. It involves calculating the number of participants needed to achieve reliable results, considering factors like expected effect size, significance level (alpha), and statistical power (1-beta). Proper estimation minimizes the risk of Type I and Type II errors, enhancing the study's credibility. An underpowered study may miss significant findings, while an overpowered study wastes resources and unnecessarily burdens participants. Thus, accurate sample size estimation is essential for conducting ethical, efficient, and scientifically valid research.

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