The p-value criterion is almost universally used in scientific research as a means of establishing statistical significance. However, it is well-known that the criterion has a number of deficiencies as a decision rule. Sole reliance on this single criterion has caused a number of problems in research credibility and integrity: see the statements of the American Statistical Association (Wasserstein and Lazar, 2016).
In this post, I introduce a number of alternatives to the p-value criterion, which can deliver more sensible statistical decisions, with an application and R code.
For the full post, please go to this link:
https://medium.com/@jaekim8080/alternatives-to-the-p-value-criterion-for-statistical-significance-with-r-code-222cfc259ba7
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