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Discussion on "statistical solutions for interdisciplinary problem-solving".

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Title: Discussion on "statistical solutions for interdisciplinary problem-solving".
Authors: Guo, Qing1 (AUTHOR), Xie, Kexin1 (AUTHOR) kexinx@vt.edu, Deng, Xinwei1 (AUTHOR) xdeng@vt.edu
Source: Quality Engineering. 2026, Vol. 38 Issue 1, p47-51. 5p.
Subjects: Interdisciplinary research, Statisticians, Quantitative research, Malaria, Cooperativeness, Prediction models
Abstract: The article discusses the role of statisticians in interdisciplinary problem-solving, emphasizing the integration of technical skills and effective communication. It highlights three key areas where statisticians contribute: the development of statistical methods for interdisciplinary challenges, modernization of classical concepts to address contemporary issues, and the application of predictive analytics for informed decision-making. The authors illustrate these points through examples, including the BOHEMIA project, which aims to combat malaria transmission using ivermectin and showcases the necessity of collaboration across various fields such as public health, entomology, and economics. The article underscores the importance of interdisciplinary approaches in enhancing the effectiveness of statistical applications in real-world scenarios. [Extracted from the article]
Copyright of Quality Engineering is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 191012102
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PubType: Academic Journal
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  Label: Title
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  Data: Discussion on "statistical solutions for interdisciplinary problem-solving".
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Guo%2C+Qing%22">Guo, Qing</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xie%2C+Kexin%22">Xie, Kexin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> kexinx@vt.edu</i><br /><searchLink fieldCode="AR" term="%22Deng%2C+Xinwei%22">Deng, Xinwei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> xdeng@vt.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22Quality+Engineering%22">Quality Engineering</searchLink>. 2026, Vol. 38 Issue 1, p47-51. 5p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Interdisciplinary+research%22">Interdisciplinary research</searchLink><br /><searchLink fieldCode="DE" term="%22Statisticians%22">Statisticians</searchLink><br /><searchLink fieldCode="DE" term="%22Quantitative+research%22">Quantitative research</searchLink><br /><searchLink fieldCode="DE" term="%22Malaria%22">Malaria</searchLink><br /><searchLink fieldCode="DE" term="%22Cooperativeness%22">Cooperativeness</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The article discusses the role of statisticians in interdisciplinary problem-solving, emphasizing the integration of technical skills and effective communication. It highlights three key areas where statisticians contribute: the development of statistical methods for interdisciplinary challenges, modernization of classical concepts to address contemporary issues, and the application of predictive analytics for informed decision-making. The authors illustrate these points through examples, including the BOHEMIA project, which aims to combat malaria transmission using ivermectin and showcases the necessity of collaboration across various fields such as public health, entomology, and economics. The article underscores the importance of interdisciplinary approaches in enhancing the effectiveness of statistical applications in real-world scenarios. [Extracted from the article]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Quality Engineering is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/08982112.2025.2512777
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 5
        StartPage: 47
    Subjects:
      – SubjectFull: Interdisciplinary research
        Type: general
      – SubjectFull: Statisticians
        Type: general
      – SubjectFull: Quantitative research
        Type: general
      – SubjectFull: Malaria
        Type: general
      – SubjectFull: Cooperativeness
        Type: general
      – SubjectFull: Prediction models
        Type: general
    Titles:
      – TitleFull: Discussion on "statistical solutions for interdisciplinary problem-solving".
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            NameFull: Guo, Qing
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            NameFull: Xie, Kexin
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            – D: 01
              M: 01
              Text: 2026
              Type: published
              Y: 2026
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              Value: 38
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            – TitleFull: Quality Engineering
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