Percentage error, in some cases, could be huge. If said scale was inaccurate enough to measure an object whose weight is similar to its error, percent error could be over 1.
I suppose it would depend on the things being weighed. If the error depended on the object being measured, it would be...
The overall goal is to create a normal distribution which can be used to visually describe the accuracy and precision of something, when the 'something' is used on a multitude of different objects.
Granted, the ball-rate-measuring-machine was an example. One could use anything that can measure...
On an added note, how would you create a single normal distribution of the machine's readings when the machine reads different balls?
EDIT: And yes, it's best to assume the machine as a black box with the same precision no matter how long it's been looking at a ball.
Let's assume there's a magical ball that bounces once every .5 seconds, and that there was a specific machine designed to calculate the rate of the ball's bounce (with error). After performing numerous readings of the ball's bounce using this machine, you have a collection of values describing...