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Understanding Statistical Hypothesis Testing: The Logic of Statistical Inference

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Original languageEnglish
Pages (from-to)945-962
JournalMachine Learning and Knowledge Extraction
Issue number3
Publication statusPublished - 12 Aug 2019
Publication typeA1 Journal article-refereed


Statistical hypothesis testing is among the most misunderstood quantitative analysis methods from data science. Despite its seeming simplicity, it has complex interdependencies between its procedural components. In this paper, we discuss the underlying logic behind statistical hypothesis testing, the formal meaning of its components and their connections. Our presentation is applicable to all statistical hypothesis tests as generic backbone and, hence, useful across all application domains in data science and artificial intelligence.

Publication forum classification

Field of science, Statistics Finland

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