# accuracy

točnost

In measurement of a set, **accuracy** is closeness of the measurements to a specific value, while **precision** is the closeness of the measurements to each other.

*Accuracy* has two definitions:

- More commonly, it is a description of
*systematic errors*, a measure of statistical bias; low accuracy causes a difference between a result and a "true" value. ISO calls this*trueness*. - Alternatively, ISO defines accuracy as describing a combination of both types of observational error above (random and systematic), so high accuracy requires both high precision and high trueness.

*Precision* is a description of *random errors*, a measure of statistical variability.

In simpler terms, given a set of data points from repeated measurements of the same quantity, the set can be said to be *accurate* if their average is close to the *true value* of the quantity being measured, while the set can be said to be *precise* if the values are close to each other. In the first, more common definition of "accuracy" above, the two concepts are independent of each other, so a particular set of data can be said to be either accurate, or precise, or both, or neither.