1) Accuracy refers to clustering of data about a known target. It is the difference between a physical quantity's average measurements and that of a known standard, accepted "truth," vs. "benchmark." Envision a target with many arrows circling the bullseye, however, none of them are near each other.

2) Precision refers to the tightness of the cluster of data. Envision a target with a cluster of arrows all touching one another but located slightly up and to the right of the bullseye.

In practice it is easier to correct a process which has good precision than it is to correct a process which is accurate. This is due to the increased amount of variation associated with accurate but not precise process.