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There's also the thing where the 1 in 0.0491 has the exact same significance as the 2 in 0.0982.

IOW, the final significant figure has continuously variable significance (but discretely intervalled numerically) depending on the absolute value of what is it supposed to be significant to.

This is a feature of granularity.

And rounding error has a variable influence on the intervals and how "discreet" or blatant any error may appear.

Then you've got error propagation and pretty soon you're going to need something like Gustafson's UNUM's:

https://en.wikipedia.org/wiki/Unum_(number_format)



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