Ouyou toukeigaku
Online ISSN : 1883-8081
Print ISSN : 0285-0370
ISSN-L : 0285-0370
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Volume 52, Issue 1
Displaying 1-4 of 4 articles from this issue
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Forum
  • Statistical Modelling, Exploration, and Society
    Hiroshi Maruyama
    Article type: Forum
    2023 Volume 52 Issue 1 Pages 1-11
    Published: 2023
    Released on J-STAGE: January 20, 2024
    DOIhttps://doi.org/10.5023/jappstat.52.1
    JOURNAL RESTRICTED ACCESS
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    Statistical modeling and exploration (or optimization) are two essential components in modern data science. Statistical modeling uses empirical knowledge (training data) to model the target system and considers the uncertainties as random noise. Exploration uses prior knowledge to model the target system, represented as a combination of boundary conditions and objective functions, and the unexplored regions are considered as uncertainties. In real-world scenarios, the objective function, which represents people's values, often becomes the major source of uncertainty. In this paper, we reexamine various approaches in data science from the perspective of "how to represent knowledge and address uncertainty" and discuss the challenges of applying them in our society. We also touch upon non-technical approaches such as agile development and TEAL organizations as methods for dealing with uncertainties in societal values.

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  • Utilization of Dynamic Population Data in Disasters
    [in Japanese]
    Article type: Forum
    2023 Volume 52 Issue 1 Pages 13-20
    Published: 2023
    Released on J-STAGE: January 20, 2024
    DOIhttps://doi.org/10.5023/jappstat.52.13
    JOURNAL RESTRICTED ACCESS
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Essay by honorary member
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