Null hypothesis

Quantum mechanics

Philosophy

Ecology

Biology

Statistics

Computer science

Simple (philosophy)

Obstacle

Physics

Psychology

Mathematics

Statistical hypothesis testing

Political science

Value (mathematics)

Epistemology

Econometrics

Data science

Rewriting

Programming language

Cutoff

Machine learning

Criticism

Despite much criticism, black-or-white null-hypothesis significance testing with an arbitrary P-value cutoff still is the standard way to report scientific findings. One obstacle to progress is likely a lack of knowledge about suitable alternatives. Here, we suggest language of evidence that allows for a more nuanced approach to communicate scientific findings as a simple and intuitive alternative to statistical significance testing. We provide examples for rewriting results sections in research papers accordingly. Language of evidence has previously been suggested in medical statistics, and it is consistent with reporting approaches of international research networks, like the Intergovernmental Panel on Climate Change, for example. Instead of re-inventing the wheel, ecology and evolution might benefit from adopting some of the 'good practices' that exist in other fields.

Rewriting results sections in the language of evidence