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So the need for an objective account of randomness of a sequence of outcomes is necessary for reliable scientific inference.
The only way to resist this counterexample is to refuse to acknowledge that such a sequence of outcomes can be an appropriate sequence in RCT.
A sequence of outcomes is an ordered collection of events, finite or infinite, such that each event is of a type in O.
It shows that the larger the value of EQI for an evidence stream, the more likely that stream is to produce a sequence of outcomes that yield a very small likelihood ratio value.
Directional Agreement means that the evidential import of hypotheses is similar enough for Pα and Pβ that a sequence of outcomes may favor a hypothesis according to Pα only if it does so for Pβ as well.
Nevertheless if such a sequence of outcomes did occur, it would have happened by chance assuming, plausibly, that if each individual outcome happens by chance, the complex event composed by all of them also happens by chance.
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But chance should not be identified with frequency since a fair coin can produce any sequence of outcomes, there is no possibility of identifying chance with observed frequency.
To compare the ratings between symptom categories, a mixed-effects logistic regression model was used in order to avoid over-dispersion of a sequence of binary outcomes within the same symptom category by a participant.
So it seems that if a world contains a random sequence of outcomes, the best theory will be one which involves probabilities, and in virtue of being part of the best theory, those probabilities will be chances.
The observation of a random sequence of outcomes is a defeasible incentive to inquire into the physical basis of the outcome sequence, and it provides at least a prima facie reason to think that a process is chancy (though recall §4.5).
This is weaker than Bernoulli (since the states of a Bernoulli system are probabilistically independent if there is any time between them), but still strong enough to plausibly yield a random sequence of outcomes from a coarse grained partition of the state space, sampled infrequently enough.
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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