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Understanding Statistical Hypothesis Testing: The Logic of Statistical Inference

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Predictive Society and Data Analytics Lab, Faculty of Information Technology and Communication Sciences, Tampere University, 33100 Tampere, Finland
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Institute of Biosciences and Medical Technology, Tampere University, 33520 Tampere, Finland
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Institute for Intelligent Production, Faculty for Management, University of Applied Sciences Upper Austria, Steyr Campus, 4040 Steyr, Austria
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Department of Mechatronics and Biomedical Computer Science, University for Health Sciences, Medical Informatics and Technology (UMIT), 6060 Hall, Tyrol, Austria
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College of Computer and Control Engineering, Nankai University, Tianjin 300000, China
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Author to whom correspondence should be addressed.
Mach. Learn. Knowl. Extr. 2019, 1(3), 945-961; https://doi.org/10.3390/make1030054
Received: 27 July 2019 / Revised: 7 August 2019 / Accepted: 9 August 2019 / Published: 12 August 2019
(This article belongs to the Section Learning)
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. View Full-Text
Keywords: hypothesis testing; machine learning; statistics; data science; statistical inference hypothesis testing; machine learning; statistics; data science; statistical inference
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Emmert-Streib, F.; Dehmer, M. Understanding Statistical Hypothesis Testing: The Logic of Statistical Inference. Mach. Learn. Knowl. Extr. 2019, 1, 945-961.

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