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The discrepancy between observed and expected values can be ascribed to the fact that the poisson expectation assumes equal gene length sequence for all genes, a clearly untrue assumption, particularly for the human genome.
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Sadly, fully understanding a standard can sometimes be difficult, and misunderstandings can allow decisions to be made on untrue assumptions about a standard.
Despite being untrue, this assumption was more than enough cause for censure for some of the open-minded young women at Clemson, since, obviously, it was "not normal".
Data from the human genome in the last decade has shown this assumption is untrue: The fingerprints of natural selection are visible across at least 10 percent of the genome.
That assumption is untrue.
Plausible scenarios where this assumption is untrue do exist.
I knew whenever I saw that photo that I would be reading something horrible and untrue about me, making assumptions about who I was and what I was looking for when it came to simply living my life.
Usually at least one of these two assumptions is untrue because the expected absolute risk reduction resulting from treatment often depends on the characteristics of individual patients.
However, in the event that either of these assumptions is untrue, we will consider sensitivity analyses to investigate the effect of the receiving of the intervention as intended, and of imputing missing outcome data.
I find this as untrue and as racist an assumption as the parent who could not think her school district hired a teacher of color.
But both these assumptions are observably untrue, largely due to appropriability and time-horizons problems.
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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