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http://repository.hneu.edu.ua/handle/123456789/28513
Полная запись метаданных
Поле DC | Значение | Язык |
---|---|---|
dc.contributor.author | Kolgatin O. | - |
dc.contributor.author | Kolgatina L. | - |
dc.contributor.author | Ponomareva N. | - |
dc.date.accessioned | 2023-01-04T12:54:16Z | - |
dc.date.available | 2023-01-04T12:54:16Z | - |
dc.date.issued | 2022 | - |
dc.identifier.citation | Kolgatin O. Stochastic process computational modeling for learning research / O. Kolgatin, L. Kolgatina, N. Ponomareva // Educational Dimension. – 2022. – Р. 68-83. | ru_RU |
dc.identifier.uri | http://repository.hneu.edu.ua/handle/123456789/28513 | - |
dc.description.abstract | The goal of our research was to compare and systematize several approaches to non-parametric null hypothesis significance testing using computer-based statistical modeling. For teaching purposes, a statistical model for simulation of null hypothesis significance testing was created. The results were analyzed using Fisher’s angular transformation, Chi-square, Mann-Whitney, and Fisher’s exact tests. Appropriate software was created, allowing us to recommend new illustrative materials for expressing the limitations of the tests that were examined. Learning investigations as a technique of comprehending inductive statistics has been proposed, based on the fact that modern personal computers can run simulations in a reasonable amount of time with great precision. The collected results revealed that the most often used non-parametric tests for small samples have low power. Traditional null hypothesis significance testing does not allow students to analyze test power because the true differences between samples are unknown. As a result, in Ukrainian statistical education, including PhD studies, the emphasis must shift away from null hypothesis significance testing and toward statistical modeling as a modern and practical approach of establishing scientific hypotheses. This finding is supported by scientific papers and the American Statistical Association’s recommendation. | ru_RU |
dc.language.iso | en | ru_RU |
dc.subject | computational modelling | ru_RU |
dc.subject | computer-based simulation | ru_RU |
dc.subject | statistical hypothesis significance testing | ru_RU |
dc.subject | education | ru_RU |
dc.subject | learning research | ru_RU |
dc.title | Stochastic processes computational modelling for learning research | ru_RU |
dc.type | Article | ru_RU |
Располагается в коллекциях: | Статті (ІС) |
Файлы этого ресурса:
Файл | Описание | Размер | Формат | |
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Кафедра_IС_Колгатiн_О.Г._стаття5_2022.pdf | 622,55 kB | Adobe PDF | Просмотреть/Открыть |
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