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But what if test design is also to blame?
What if test results found something I did not want to know, like evidence that the disease was spreading?
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Most any major financial decision can be assessed by applying the "what-if?" test.
For instance, in the field of finance, the network models are very popular and the proposed methodology allows to carry out "what if" tests in terms of weakening the links between the economic agents, represented as nodes.
What if the test results did not make it to the clinical trial office in time for the appointment - making our drive for naught?
What if a test or task seems particularly whacky?
But what if the test doesn't serve that purpose or worse, skews the perception of a student's ability?
"What if someone tests negative, and they don't have the marker, so they think that means they can drink more?
'What if we tested for 3 months instead of 6 months,' etc".
In addition, this platform allows scientists to simulate and analyze the models in real-time on the web, including the ability to simulate loss/gain of function and test what-if scenarios in real time.
The latter (i.e., expert-driven) is not automatically built from data but instead involves experts who directly articulate a set of assumptions, which can easily be altered to test what-if scenarios such as the expected consequences if an intervention was to be put to practice.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com