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In junior high, the three were principals of the Wolf Club, which was devoted to girls — a largely hypothetical subject, at the time, for all three.
The incidence of real and hypothetical subject presence in each bucket or pixel was compared to a Gaussian distribution, in a t-statistic analysis.
Consider a hypothetical subject who forgets the length of L1, but has no ambiguity about the length of L2, i.e., the neural representation of L1 is infinitely noisy whereas there is no noise in the neural representation of L2.
For the range-matched uniform noise simulation, the assumption of a linearly uniform spectrum density meant that each hypothetical subject produced a keypress range that was the same as their matched real subject, with a distribution that was uniform across this range.
For the mean-matched uniform noise simulation, this meant that each hypothetical subject produced keypress results within the range of the 95% confidence interval of their matched real experimental subject; for some subjects, the lower limit of the confidence interval would be below zero, in which case the theoretical values below zero would be considered to be zero.
A hypothetical subject cohort of 884,000 was followed until all had died.
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Studying what and how people eat is a messy science, in large part because it's extremely difficult to control human behavior: in 2016, the British epidemiologist Ben Goldacre, discussing obstacles to his ideal experiment, noted, of its hypothetical subjects, "I would have to imprison them all, because there's no way I would be able to force 500 people to eat fruits and vegetables for a life".
These hypothetical subjects could decompose the audio signals and independently measure the levels of impairment due to MNRU and T-Reference relative to the best audio quality in the experiment ( and ): (14).
The predictive distribution of the outcomes for a set I of hypothetical subjects i∗ was defined as ( C i ∗ k Z, C i ∗ k P, E i ∗ k ) i ∗ ∈ I | data = ∫ p θ data ∏ i ∗ p U i ∗ θ × ∏ k P C i ∗ k Z β k Z, X i ∗ k Z p C i ∗ k P X i ∗ k P, β k P, U i ∗ P, τ DSQ i ∗ k × p E i ∗ k X i ∗ k E, β k E, U i ∗ E, σ E, DSQ i ∗ k 2 d U i ∗ d θ. (11).
The collected behaviors of the hypothetical subjects for each parameterization were compared with those of the experimental subjects.
The sample size of 40 hypothetical subjects is based on the following considerations.
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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