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Does Information Theory Provide a New Paradigm for Earth Science? Hypothesis Testing
Author(s) -
Nearing Grey S.,
Ruddell Benjamin L.,
Bennett Andrew R.,
Prieto Cristina,
Gupta Hoshin V.
Publication year - 2020
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2019wr024918
Subject(s) - inference , computer science , perspective (graphical) , value of information , statistical hypothesis testing , information theory , field (mathematics) , data science , artificial intelligence , mathematics , statistics , pure mathematics
Model evaluation and hypothesis testing are fundamental to any field of science. We propose here that by changing slightly the way we think and communicate about inference—from being fundamentally a problem of uncertainty quantification to being a problem of information quantification—allows us to avoid certain problems related to testing models as hypotheses. We propose that scientists are typically interested in assessing the information provided by models, not the truth value or likelihood of a model. Information theory allows us to formalize this perspective.