Statistical Analysis Dataset Based on Taguchi Design and Regression Modelingdoi:10.48788/DVUA/BKCZOADataverseUA2026-01-161Kolesnyk, Vitalii; Dovhopolov, Andrii; Andrii Deineka, 2026, "Statistical Analysis Dataset Based on Taguchi Design and Regression Modeling", https://doi.org/10.48788/DVUA/BKCZOA, DataverseUA, V1Statistical Analysis Dataset Based on Taguchi Design and Regression Modelingdoi:10.48788/DVUA/BKCZOAKolesnyk, VitaliiDovhopolov, AndriiAndrii DeinekaMinitab0124U000538DataverseUAKolesnyk, VitaliiKolesnyk, Vitalii2026-01-14Engineeringstatistical analysisRegressionSignal/Noise AnalysisCoefficientsAnalysis of variancesThe 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.tabular arraystatistical analysisWithin the statistical analysis, the controlling factors influencing the response characteristics were considered, specifically the number of smoke elements, air flow velocity, humidity, and atmospheric pressure. The factors were varied at discrete levels according to the Taguchi orthogonal plan, which ensured a reduction in the number of calculation combinations while maintaining the informativeness of the analysis. The ambient temperature was considered as an external parameter and was analyzed separately for each temperature regime. In the Minitab software environment, calculations of signal-to-noise ratios, analysis of main effects, assessment of factor contributions, and construction of regression models that account for physically justified interactions were performed. The data can be used to check the sensitivity of the results to the choice of factors and settings of statistical models.Kolesnyk, Vitalii; Andrii Dovhopolov, 2026, "Results of Experimental–Numerical Modeling of Smoke Flow under Various Temperature Conditions", https://doi.org/10.48788/DVUA/9HBL0K, DataverseUA, V110.48788/DVUA/9HBL0KKolesnyk, Vitalii; Andrii Dovhopolov, 2026, "Results of Experimental–Numerical Modeling of Smoke Flow under Various Temperature Conditions", https://doi.org/10.48788/DVUA/9HBL0K, DataverseUA, V1Kolesnyk, Vitalii; Dovhopolov, Andrii; Andrii Deineka, 2026, "Smoke flow design to experiment_FEM", https://doi.org/10.48788/DVUA/JAO7E6, DataverseUA, V110.48788/DVUA/JAO7E6Kolesnyk, Vitalii; Dovhopolov, Andrii; Andrii Deineka, 2026, "Smoke flow design to experiment_FEM", https://doi.org/10.48788/DVUA/JAO7E6, DataverseUA, V1Processing FEM_Results.mpxMinitab 19 fileapplication/octet-stream