Statistical Analysis Dataset Based on Taguchi Design and Regression Modeling (doi:10.48788/DVUA/BKCZOA)

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Part 2: Study Description
Part 5: Other Study-Related Materials
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Document Description

Citation

Title:

Statistical Analysis Dataset Based on Taguchi Design and Regression Modeling

Identification Number:

doi:10.48788/DVUA/BKCZOA

Distributor:

DataverseUA

Date of Distribution:

2026-01-16

Version:

1

Bibliographic Citation:

Kolesnyk, Vitalii; Dovhopolov, Andrii; Andrii Deineka, 2026, "Statistical Analysis Dataset Based on Taguchi Design and Regression Modeling", https://doi.org/10.48788/DVUA/BKCZOA, DataverseUA, V1

Study Description

Citation

Title:

Statistical Analysis Dataset Based on Taguchi Design and Regression Modeling

Identification Number:

doi:10.48788/DVUA/BKCZOA

Authoring Entity:

Kolesnyk, Vitalii (Sumy State University)

Dovhopolov, Andrii (Sumy State University)

Andrii Deineka (Sumy State University)

Software used in Production:

Minitab

Grant Number:

0124U000538

Distributor:

DataverseUA

Access Authority:

Kolesnyk, Vitalii

Depositor:

Kolesnyk, Vitalii

Date of Deposit:

2026-01-14

Holdings Information:

https://doi.org/10.48788/DVUA/BKCZOA

Study Scope

Keywords:

Engineering, statistical analysis, Regression, Signal/Noise Analysis, Coefficients, Analysis of variances

Abstract:

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.

Kind of Data:

tabular array

Kind of Data:

statistical analysis

Notes:

Within 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.

Methodology and Processing

Sources Statement

Data Access

Other Study Description Materials

Related Publications

Citation

Title:

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, V1

Identification Number:

10.48788/DVUA/9HBL0K

Bibliographic Citation:

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, V1

Citation

Title:

Kolesnyk, Vitalii; Dovhopolov, Andrii; Andrii Deineka, 2026, "Smoke flow design to experiment_FEM", https://doi.org/10.48788/DVUA/JAO7E6, DataverseUA, V1

Identification Number:

10.48788/DVUA/JAO7E6

Bibliographic Citation:

Kolesnyk, Vitalii; Dovhopolov, Andrii; Andrii Deineka, 2026, "Smoke flow design to experiment_FEM", https://doi.org/10.48788/DVUA/JAO7E6, DataverseUA, V1

Other Study-Related Materials

Label:

Processing FEM_Results.mpx

Text:

Minitab 19 file

Notes:

application/octet-stream