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This article explores the critical elements of hypothesis testing, focusing on the factors that impact statistical power and sample size. We discuss how changes in effect size, standard deviation, and significance level (alpha) can either increase or decrease the required sample size to maintain adequate power. Additionally, we analyze the implications of one-tailed versus two-tailed tests and the importance of power calculations in research. This comprehensive guide will enhance your understanding of how to properly design studies for reliable results.
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