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The phrase "a hard assumption" is correct and usable in written English.
It can be used when discussing a belief or idea that is strongly held or difficult to challenge.
Example: "Making a hard assumption about the project's timeline could lead to unrealistic expectations."
Alternatives: "a strong assumption" or "a firm assumption".
Exact(1)
At the time of this study it was a hard assumption, as the vaccine was available at the start of June 2008 and the first outbreaks in previous 2006 and 2007 were observed at the start of August and at the end of July: leaving 8 weeks to vaccinate the population.
Similar(59)
I think White people get very defensive talking about these issues but it benefits everyone if we are each willing to take a hard look at our assumptions and biases.
We must all take a hard look at our assumptions, engage the academic community in searching for evidence of what works and what doesn't, challenge what we think we know about the problem and begin to have conversations that will be uncomfortable for some.
It is a"soft modeling" approach requiring very few distributional assumptions, variables can be numerical, ordinal or nominal, and no need for normality assumptions, while covariance-based SEM is a "hard modeling" with heavy distribution assumptions.
That 20 percent figure, however, is as much an assumption as a hard data point — it is challenging to calibrate these figures until one knows exactly how many voters turned out.
Here's an example: Central banks' principal models before the financial crisis, the so-called DSGE models, made a crucial assumption, hard as it is to believe, that economies are always in instantaneous equilibrium.
Not surprisingly, a moment arrives when Elliot casts off his "factory-set" anxieties, a hard-cased set of Western assumptions, and trusts to luck and his own good sense.
Using this hard prior assumption, the variance of outlier class is completely determined by the variance of the normal class.
Importantly though, the hard-coded assumption in a game like Go is that we want to win!
Many existing prediction approaches model concurrent behaviour insufficiently and yield inaccurate results due to hard underlying assumptions.
Such an assumption seems hard to support: a black person in New York who is stopped by the police is 24% more likely to have a gun pointed at them than a white person, so why would they be no less likely to be shot by an officer?
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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