Modern State of Statistical Hypotheses Testing and Perspectives of its Development

Kachiashvili Kj
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Kachiashvili Kj: Faculty of Informatics and Control Systems, Georgian Technical University, Georgia

Biostatistics and Biometrics Open Access Journal, 2019, vol. 9, issue 2, 41-44

Abstract: A statistical hypothesis is a formalized record of properties of the investigated phenomenon and relevant assumptions. The statistical hypotheses are set when random factors affect the investigated phenomena, i.e. when the observation results of the investigated phenomena are random. The properties of the investigated phenomenon are completely defined by its probability distribution law. Therefore, the statistical hypothesis is an assumption concerning this or that property of the probability distribution law of a random variable. Mathematical statistics is the set of the methods for studying the events caused by random variability and estimates the measures (the probabilities) of possibility of occurrence of these events. For this reason, it uses distribution laws as a rule. Practically all methods of mathematical statistics one way or another, in different doses, use hypotheses testing techniques. Therefore, it is very difficult to overestimate the meaning of the methods of statistical hypotheses testing in the theory and practice of mathematical statistics.

Keywords: Biometrics Open Access Journal; Biostatistics and Biometrics; Biostatistics and Biometrics Open Access Journal; Open Access Journals; biometrics journal; biometrics articles; biometrics journal reference; biometrics journal impact factor; biometrics and biostatistics journal impact factor; journal of biometrics; open access juniper publishers; juniper publishers reivew (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:adp:jbboaj:v:9:y:2019:i:2:p:41-44

DOI: 10.19080/BBOAJ.2019.09.555759

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