Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Proceedings of the 2022 International Conference on Financial Technology and Business Analysis (ICFTBA 2022), Part 2
Series Vol. 6 , 27 April 2023
Open
Access | Article
Development and Comparison of Regression Models Predicting Wine Quality using Excel - From a Profit Maximization Perspective
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Abstract
Wine reviewers and the general public usually determine the quality of the wine. There is a great deal of subjec-tivity in such reviews and differences in the reviewers' preferences, making it difficult for the winery to obtain favorable information. This paper will use Excel to build a related model of chemical substances in wine and wine quality. Both linear and logistic regression is used in this article to predict wine quality. In addition, differ-ent from past literature that indicates the quality of red wine based on chemical substances, this paper creatively constructs a profit model based on predicting wine quality. It thus helps wine sellers to make model selections. All these can help producers understand how to make good wine and get higher profits.
Keywords
linear regression, logistic regression, wine quality, profit maximization
References
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2022 International Conference on Financial Technology and Business Analysis (ICFTBA 2022), Part 2
- ISBN (Print)
- 978-1-915371-23-2
- ISBN (Online)
- 978-1-915371-24-9
- Published Date
- 27 April 2023
- Series
- Advances in Economics, Management and Political Sciences
- ISSN (Print)
- 2754-1169
- ISSN (Online)
- 2754-1177
- DOI
- 10.54254/2754-1169/6/20220140
- Copyright
- 27 April 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited