Abstract
A multifactor model of the behavior of a population of biological objects is described. The model considers the structure of repeated observations and does not assume there are classical requirements for the independence of observations, their normality, or correlation homogeneity. Hypotheses about there being no influence of intergroup and intragroup factors on measured characteristics of biological objects are formulated, and modern statistical criteria for testing hypotheses with no classical assumptions and different sample sizes are described. Results from theoretical studies are used to create a program module for the statistical processing of experimental data in studying the behavior of a population of biological objects that depend on several factors. A three-factor model of their behavior is constructed on the basis of real experimental data on the behavior of a population of Ixodidae ticks,depending on their habitat,ambient temperature, and time of day.
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Translated by E. Oborin
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Belov, A.G., Polienko, A.E. & Belova, O.A. Multifactor Modeling and Analysis of Repeated Observations of Biological Objects. MoscowUniv.Comput.Math.Cybern. 45, 45–52 (2021). https://doi.org/10.3103/S0278641921020011
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DOI: https://doi.org/10.3103/S0278641921020011