What is it about?

The crisis in statistics — including calls for scientists to abandon statistical significance — should inspire a similar re-think of mathematical modelling,

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Why is it important?

Unlike statistics, mathematical modelling is not a discipline. It cannot discuss possible fixes in disciplinary fora under the supervision of recognised leaders. It cannot issue authoritative statements of concern from relevant institutions such as e.g., the American Statistical Association or the columns of Nature. Hence existing problems risk remaining unaddressed. See e.g. some of the problems here: https://growkudos.com/publications/10.1016%25252Fj.envsoft.2019.01.012/reader

Perspectives

Mathematical modelling could benefit from structure and standards based on statistical principles including a systemic appraisal of model uncertainties and parametric sensitivities. Statistics could help by internalising these into its own syllabi and practices. Perhaps what is needed is a new ethics of quantification. An oncoming symposium at the University of Bergen is addressing the theme, https://www.uib.no/en/svt/127044/ethics-quantification.

Professor Andrea Saltelli
University Pompeo Fabra, Barcelona School of Management

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This page is a summary of: A short comment on statistical versus mathematical modelling, Nature Communications, August 2019, Springer Science + Business Media,
DOI: 10.1038/s41467-019-11865-8.
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