The Extremist unipolar (ëu)
A Simple Way of Measuring Difference on Unipolar Data in A/B Testing. The Hawk-Eye Way.
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"The Extremist unipolar (ëu): A Simple Way of Measuring Difference on Unipolar Data in A/B Testing. The Hawk-Eye Way" introduces a new methodological framework called "modular statistics", offering a unified and structural approach to inference that departs from both the frequentist and Bayesian traditions. Conceived as an alternative to p-values, the method quantifies structural truth as the measurable difference between bounded systems, where data are not random noise to be averaged but organized evidence to be understood. It represents a third (objective) statistical path that favors clari...
"The Extremist unipolar (ëu): A Simple Way of Measuring Difference on Unipolar Data in A/B Testing. The Hawk-Eye Way" introduces a new methodological framework called "modular statistics", offering a unified and structural approach to inference that departs from both the frequentist and Bayesian traditions. Conceived as an alternative to p-values, the method quantifies structural truth as the measurable difference between bounded systems, where data are not random noise to be averaged but organized evidence to be understood. It represents a third (objective) statistical path that favors clarity, bounded reasoning, and interpretability over arbitrary thresholds and prior beliefs. Reviewed by three experts: a mathematician, a public health specialist, and a clinical radiologist, it ensures mathematical rigor, interdisciplinary coherence, and biomedical relevance. Spanning 124 pages, this Digest Edition unfolds as a scientific treatise including a foreword, 17 figures, 36 references, an afterword, and a detailed index. Published under the KUNA Label (Medicinarium d.o.o.), this groundbreaking volume stands as both a methodological manifesto and a scientific instrument. Offering libraries, scientists, and educators a precise and human-centered path toward a redefined science of measurement and inference. It is applicable across statistics, artificial intelligence, data science, biomedical research, and evidence synthesis. The Truth Bubble says: "No guess. Just yess!"
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