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So, an evidence stream that favors hi according to Pα may instead favor hj according to Pβ.
First, notice that if there is a crucial experiment in the evidence stream, the theorem is completely obvious.
The Falsification Theorem applies whenever the evidence stream includes possible outcomes that may falsify the alternative hypothesis.
It completely ignores the influence of any experiments or observations in the evidence stream on which hypothesis hj is fully outcome-compatible with hypothesis hi.
That is, it applies to all evidence streams for which hj is fully outcome-compatible with hi on each ck in the evidence stream.
Hypotheses whose connection with the evidence is entirely statistical in nature will inevitably be fully outcome-compatible on the entire evidence stream.
Similar(30)
Evidence streams of this kind contain no possibly falsifying outcomes.
It applies to all evidence streams not containing possibly falsifying outcomes for hj.
Figure 7 A specimen time-stepping BBN for Santorini unrest, with four evidence streams.
It applies to all evidence streams not containing possibly falsifying outcomes for hj when hi holds i.e., it applies to all evidence streams for which hj is fully outcome-compatible with hi on each ck in the stream.
We now turn to a theorem that applies to those evidence streams (or to parts of evidence streams) consisting only of experiments and observations on which hypothesis hj is fully outcome-compatible with hypothesis hi.
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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