# Accuracy and precision

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Accuracy, in science, engineering, industry and statistics, is the degree of conformity of a measured/calculated quantity to its actual (true) value. Precision (also called reproducibility or repeatability) is the degree to which further measurements or calculations will show the same or similar results.

The results of a measurement or calculations can be accurate but not precise, precise but not accurate, neither, or both; if a result is both accurate and precise, it is called valid.

The related terms in surveying are error (random variability in research) and bias (nonrandom or directed effects caused by a factor or factors unrelated by the independent variable).

## The target analogy

By far the most common analogy used to explain the concept is the target comparison.

Repeated measurements are compared to arrows that are fired at a target. Accuracy describes the closeness of arrows to the bullseye at the target center. Arrows that strike closer to the bullseye are considered more accurate. The closer a system's measurements to the accepted value, the more accurate the system is considered to be.

To continue the analogy, if a large number of arrows are fired, precision would be the size of the arrow cluster. (When only one arrow is fired, precision is the size of the cluster one would expect if this was repeated many times under the same conditions.) When all arrows are grouped tightly together, the cluster is considered precise since they all struck close to the same spot, if not necessarily near the bullseye. The measurements are precise, though not necessarily accurate.

However, it is not possible to reliably achieve accuracy in individual measurements without precision - if the arrows are not grouped close to one another, they cannot all be close to the bullseye. (Their average position might be an accurate estimation of the bullseye, but the individual arrows are inaccurate.)

Accuracy is the degree of veracity while precision is the degree of reproducibility.