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"It's the law of small numbers," said Martin Connor, a former Democratic state senator and campaign lawyer.
When we wrote our first paper, "The Law of Small Numbers", we were laughing all the time we wrote it.
One of these biases, which the psychologists Daniel Kahneman and Amos Tversky pointed out decades ago, is sometimes referred to as the "law of small numbers".
This problem is compounded by the tendency to extrapolate big conclusions from small samples, something that behavioral economists call "the law of small numbers".
The result is a different kind of approximation to the binomial distribution, called the Poisson distribution (after the French mathematician Siméon-Denis Poisson) or the law of small numbers.
Their first paper was about how people were routinely drawn to extrapolating conclusions from statistically insignificant samples: "Belief in the Law of Small Numbers" – a faith that if a coin came down heads twice in a row, the next toss was more likely to be tails.
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Linda J. Blumberg, an Urban Institute researcher, said, "Contrary to a lot of statements that have been made in the press and elsewhere, the impact of the law on small employers is going to be positive in great degree".
The derived gains are easy to be scheduled since the scheduling law consists of small number of grid points and requires just linear interpolation calculation.
The law of the small world.
In part I we learned about the law of the small world and the law of first mover advantage.
This is where the Law of the Small World comes in: Information about jobs is possibly best found through hubs.
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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