Abstract
This study applies multiple linear regression analysis to investigate the correlation between electric vehicle exterior design and emotional vocabulary, with an emphasis on its educational application. We selected six primary automotive features as independent variables (X) and compiled consumer emotional response data toward various design features as dependent variables (Y). Multiple linear regression analysis was performed, with the F-test results showing an F-value of 5.198 and a p-value less than 0.05, indicating significant predictive ability. Some independent variables exhibited significant effects on the dependent variables based on t-test results (p<0.05), demonstrating that these variables significantly impact the dependent variables. model passed normality (shapiro-wilk test, p=0.976) and independence tests (durbin-watson value=1.838) without issues of multicollinearity, ensuring its robustness explanatory power. subsequent validation confirmed significance stability. results indicate is effective in examining influence design features on emotional vocabulary, offering practical insights for designers educational applications. additionally, it serves as a tool to enhance students' analysis capabilities.
Author Information
Yi-Wun Wang, National Cheng Kung University, Taiwan
Meng-Dar Shieh, National Cheng Kung University, Taiwan
Paper Information
Conference: IICE2025
Stream: Design
This paper is part of the IICE2025 Conference Proceedings (View)
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To cite this article:
Wang Y., & Shieh M. (2025) Educational Research on the Application of Multiple Linear Regression Analysis to the Relationship Between Electric Vehicle Exterior Design and Affective Vocabulary ISSN: 2189-1036 – The IAFOR International Conference on Education – Hawaii 2025 Official Conference Proceedings (pp. 239-243) https://doi.org/10.22492/issn.2189-1036.2025.20
To link to this article: https://doi.org/10.22492/issn.2189-1036.2025.20
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