Understanding Statistical Hypothesis Testing: The Logic of Statistical Inference
Research output: Contribution to journal › Article › Scientific › peer-review
|Journal||Machine Learning and Knowledge Extraction|
|Publication status||Published - 12 Aug 2019|
|Publication type||A1 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.