Significant digits in a float?

[Ben Finney]

Roy Smith <roy at panix.com> writes:

> In article <mailman.9575.1398789020.18130.python-list at python.org>,
>  Chris Angelico <rosuav at gmail.com> wrote:
>
> > You have one chance in ten, repeatably, of losing a digit. That is,
> > roughly 10% of your four-decimal figures will appear to be
> > three-decimal, and 1% of them will appear to be two-decimal, and so
> > on. Is that "a few" false negatives?
>
> You're looking at it the wrong way.  It's not that the glass is 10% 
> empty, it's that it's 90% full, and 90% is a lot of good data :-)

The problem is you won't know *which* 90% is accurate, and which 10% is
inaccurate. This is very different from the glass, where it's evident
which part is good.

So, I can't see that you have any choice but to say that *any* of the
precision predictions should expect, on average, to be (10 + 1 + …)
percent inaccurate. And you can't know which ones. Is that an acceptable
error rate?

-- 
 \      “If you don't fail at least 90 percent of the time, you're not |
  `\                                    aiming high enough.” —Alan Kay |
_o__)                                                                  |
Ben Finney