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The previous articles of the Statistical Round in the Korean Journal of Anesthesiology posed a strong enquiry on the issue of null hypothesis significance testing (NHST). P values lie at the core of NHST and are used to classify all treatments into two groups: "has a significant effect" or "does not have a significant effect." NHST is frequently criticized for its misinterpretation of relationships and limitations in assessing practical importance. It has now provoked criticism for its limited use in merely separating treatments that "have a significant effect" from others that do not. Effect sizes and CIs expand the approach to statistical thinking. These attractive estimates facilitate authors and readers to discriminate between a multitude of treatment effects. Through this article, I have illustrated the concept and estimating principles of effect sizes and CIs.
Dong Kyu Lee (Fri,) studied this question.