Statistical Analysis Dataset Based on Taguchi Design and Regression Modeling

The dataset is intended for statistical analysis of the results of numerical experiments using the Taguchi design of experiments and regression analysis, as implemented in the Minitab software environment. Within the framework of data processing, Taguchi orthogonal designs were employed to assess th...

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Бібліографічні деталі
Дата:2026
Автори: Kolesnyk, Vitalii, Dovhopolov, Andrii, Andrii Deineka
Формат: Data
Опубліковано: DataverseUA 2026
Теми:
Онлайн доступ:https://doi.org/10.48788/DVUA/BKCZOA
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Назва журналу:Open Data Repository of the National Academy of Sciences of Ukraine

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Open Data Repository of the National Academy of Sciences of Ukraine
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author Kolesnyk, Vitalii
Dovhopolov, Andrii
Andrii Deineka
author2 Kolesnyk, Vitalii
author_facet Kolesnyk, Vitalii
Kolesnyk, Vitalii
Dovhopolov, Andrii
Andrii Deineka
author_sort Kolesnyk, Vitalii
collection DSpace
description The dataset is intended for statistical analysis of the results of numerical experiments using the Taguchi design of experiments and regression analysis, as implemented in the Minitab software environment. Within the framework of data processing, Taguchi orthogonal designs were employed to assess the influence of control factors, calculate signal-to-noise ratios for robustness analysis, and plot main effects and rank factors by their contribution to the response. Additionally, regression modeling was performed to establish functional dependencies between process parameters and quantitative response characteristics, to check the statistical significance of coefficients, and to analyze the adequacy of the models. The dataset can be used to reproduce the analysis, compare statistical approaches, educational goals, and further develop mathematical models in engineering problems.
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spelling doi-10-48788-DVUA-BKCZOA2026-01-17T02:00:01ZStatistical Analysis Dataset Based on Taguchi Design and Regression Modelinghttps://doi.org/10.48788/DVUA/BKCZOAKolesnyk, VitaliiDovhopolov, AndriiAndrii DeinekaDataverseUAThe dataset is intended for statistical analysis of the results of numerical experiments using the Taguchi design of experiments and regression analysis, as implemented in the Minitab software environment. Within the framework of data processing, Taguchi orthogonal designs were employed to assess the influence of control factors, calculate signal-to-noise ratios for robustness analysis, and plot main effects and rank factors by their contribution to the response. Additionally, regression modeling was performed to establish functional dependencies between process parameters and quantitative response characteristics, to check the statistical significance of coefficients, and to analyze the adequacy of the models. The dataset can be used to reproduce the analysis, compare statistical approaches, educational goals, and further develop mathematical models in engineering problems.Engineeringstatistical analysisRegressionSignal/Noise AnalysisCoefficientsAnalysis of variances2026-01-16Kolesnyk, VitaliiData
spellingShingle Engineering
statistical analysis
Regression
Signal/Noise Analysis
Coefficients
Analysis of variances
Kolesnyk, Vitalii
Dovhopolov, Andrii
Andrii Deineka
Statistical Analysis Dataset Based on Taguchi Design and Regression Modeling
title Statistical Analysis Dataset Based on Taguchi Design and Regression Modeling
title_full Statistical Analysis Dataset Based on Taguchi Design and Regression Modeling
title_fullStr Statistical Analysis Dataset Based on Taguchi Design and Regression Modeling
title_full_unstemmed Statistical Analysis Dataset Based on Taguchi Design and Regression Modeling
title_short Statistical Analysis Dataset Based on Taguchi Design and Regression Modeling
title_sort statistical analysis dataset based on taguchi design and regression modeling
topic Engineering
statistical analysis
Regression
Signal/Noise Analysis
Coefficients
Analysis of variances
url https://doi.org/10.48788/DVUA/BKCZOA
work_keys_str_mv AT kolesnykvitalii statisticalanalysisdatasetbasedontaguchidesignandregressionmodeling
AT dovhopolovandrii statisticalanalysisdatasetbasedontaguchidesignandregressionmodeling
AT andriideineka statisticalanalysisdatasetbasedontaguchidesignandregressionmodeling