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Chapter 9: Using Data-Driven Uncertainty Quantification to Support Decision Making

    https://doi.org/10.1142/9781786345400_0009Cited by:0 (Source: Crossref)
    Abstract:

    As data collection and analysis methods become increasingly sophisticated, interpretation and use of results by end users become increasingly challenging. In this paper, we discuss the role of data-driven uncertainty quantification in supporting and improving decision making. We illustrate our argument with a case study in seismic onset detection, comparing statistically computed distributions over possible signal onset times to the onset times chosen by a set of domain analysts. Importantly, the uncertainty distributions sometimes identify subtle changes in the seismic waveform that are missed by both point estimate calculations and by domain analysts.