Roy Smith <r...@panix.com> writes: > In article <mailman.9575.1398789020.18130.python-l...@python.org>, > Chris Angelico <ros...@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 -- https://mail.python.org/mailman/listinfo/python-list
