Methodological proposal demonstrates an alternative statistical testing framework for data analysis, indicating improved detection of parametric differences without unrealistic null assumptions.
The conventional procedure for null hypothesis significance testing has long been the target of appropriate criticism. A more reasonable alternative is proposed, one that not only avoids the unrealistic postulation of a null hypothesis but also, for a given parametric difference and a given error probability, is more likely to report the detection of that difference.
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Jones et al. (2000) studied this question.
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