Abstract
The quality of a modeled distribution function for describing the distribution of a set of random variables is evaluated in statistical hypothesis testing. A null hypothesis H0 is assumed, which claims the sample and the fitted probability distribution to have the same population [8]. Thereby, two errors can be made. A type I error, which is the rejection of a true null hypothesis, and a type II error, which is the non-rejection of a false null hypothesis.
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Berlinger, M. (2021). Generalized Anderson-Darling Test. In: A Methodology to Model the Statistical Fracture Behavior of Acrylic Glasses for Stochastic Simulation. Mechanik, Werkstoffe und Konstruktion im Bauwesen, vol 59. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-34330-9_3
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DOI: https://doi.org/10.1007/978-3-658-34330-9_3
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