Hypothesis testing is one of the most widely used quantitative methods in decision making. It answers a research question in terms of statistical (non-) significance of a null hypothesis. The procedure of hypothesis testing can result in several errors. This entry focuses on Type II errors, which occur when a false hypothesis is not rejected. A short introduction to hypothesis testing is provided, followed by an overview of factors influencing the occurrence of Type II errors and examples of Type II errors beyond the boundaries of statistics.
Developed by Jerzy Neyman and Egon S. Pearson, hypothesis testing has become one of the most widely used quantitative methodologies in almost all areas dealing with experiments and data. In this decision process, a simple statement or null ...
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