Are Only p-Values Less Than 0.05 Significant? A p-Value Greater Than 0.05 Is Also Significant!

Abstract

Statistical hypothesis testing compares the significance probability value and the significance level value to determine whether or not to reject the null hypothesis. This concludes “significant or not significant.” However, since this process is a process of statistical hypothesis testing, the conclusion of “statistically significant or not statistically significant” is more appropriate than the conclusion of “significant or not significant.” Also, in many studies, the significance level is set to 0.05 to compare with the significance probability value, p -value. If the p -value is less than 0.05, it is judged as “significant,” and if the p -value is greater than 0.05, it is judged as “not significant.” However, since the significance probability is a value set by the researcher according to the circumstances of each study, it does not necessarily have to be 0.05. In a statistical hypothesis test, the conclusion depends on the setting of the significance level value, so the researcher must carefully set the significance level value. In this study, the stages of statistical hypothesis testing were examined in detail, and the exact conclusions accordingly and the contents that should be considered carefully when interpreting them were mentioned with emphasis on statistical hypothesis testing and significance level. In 11 original articles published in the Journal of Lipid and Atherosclerosis in 2022, the interpretation of hypothesis testing and the contents of the described conclusions were reviewed from the perspective of statistical hypothesis testing and significance level, and the content that I would like to be supplemented was mentioned.

Beyond regression: Unpacking research of human complex systems with qualitative comparative analysis

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A model study for the classification of high-risk groups for cardiac arrest in general ward patients using simulation techniques

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