Particular Analysis of Regression Effect Sizes Applied on Big Data Set

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17450%2F24%3AA2502NWR" target="_blank" >RIV/61988987:17450/24:A2502NWR - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-53552-9_18" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-53552-9_18</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-53552-9_18" target="_blank" >10.1007/978-3-031-53552-9_18</a>

Result language
angličtina
Original language name
Particular Analysis of Regression Effect Sizes Applied on Big Data Set
Original language description
In accordance with quantitative research, a wide spectrum of techniques can be seen. In the case of cardinal variables, regression analyses are suitable tools for the expression of dependences between observed variables. One of their options, the regression coefficients have been considered. However, the effect sizes analyses have not been so widely seen in research works in general. In this contribution, the big data analysis is being presented focusing on the regression effect size behavior following changing the number of samples. Two-dimensional and three-dimensional computations are applied with utilized mathematical regression models. The stable or stochastic behavior of Cohens f squared is discussed in the particular applied quantitative research of the OECD PISA with 397708 answers from respondents.
Czech name
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Czech description
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Type
D - Article in proceedings
CEP classification
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OECD FORD branch
50301 - Education, general; including training, pedagogy, didactics [and education systems]

Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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