accuracy
See precision.
- Snippet from Wikipedia: Accuracy and precision
Accuracy and precision are two measures of observational error.
Accuracy is how close a given set of measurements (observations or readings) are to their true value.
Precision is how close the measurements are to each other.
In other words:
- Precision is a description of random errors (a measure of statistical variability).
- Accuracy has two definitions, per ISO:
- More commonly, a description of systematic errors (a measure of statistical bias of a given measure of central tendency). Low accuracy causes a difference between a result and a true value. This secondary measure is referred to as trueness by ISO.
- A combination of both types of observational error (random and systematic), so high accuracy requires both high precision and high trueness.
In the first, more common definition of "accuracy" above, the concept is independent of "precision", so a particular set of data can be said to be accurate, precise, both, or neither.
In simpler terms, given a statistical sample or set of data points from repeated measurements of the same quantity, the sample or 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 their standard deviation is relatively small.