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Understanding Statistical Hypothesis Testing: The Logic of Statistical Inference

  • Tampere University
  • Upper Austria University of Applied Sciences
  • Private University for Health Sciences, Medical Informatics and Technology
  • Nankai University

Research output: Contribution to journalReview articlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)945-962
Number of pages18
JournalMachine Learning and Knowledge Extraction
Volume1
Issue number3
DOIs
Publication statusPublished - Sept 2019
Externally publishedYes

Keywords

  • data science
  • hypothesis testing
  • machine learning
  • statistical inference
  • statistics

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