Accuracy and precision are used in context of measurement. Accuracy refers to the degree of conformity and correctness of something when compared to a true or absolute value, while precision refers to a state of strict exactness — how consistently something is strictly exact.

In other words, the precision of an experiment, object, or value is a measure of the reliability and consistency. The accuracy of an experiment, object, or value is a measurement of how closely results agree with the true or accepted value.

Both accuracy and precision are terms used in the fields of science, engineering, and statistics.

## Comparison chart

Accuracy Precision The degree of conformity and correctness of something when compared to a true or absolute value. A state of strict exactness — how often something is strictly exact. Single factor or measurement Multiple measurements or factors are needed Something can be accurate on occasion as a fluke. For something to be consistently and reliably accurate, it must also be precise. Results can be precise without being accurate. Alternatively, results can be precise AND accurate. Physics, chemistry, engineering, statistics, and so on. Physics, chemistry, engineering, statistics, and so on.

## Example

One can say that a measurement is accurate but not precise, precise but not accurate, or neither or both. An example of bad precision with good accuracy might be a lab refrigerator that holds a constant temperature of 38.0F. A temperature sensor is tested 10 times in the refrigerator. The temperatures from the test yield the temperatures of: 37.8, 38.3, 38.1, 38.0, 37.6, 38.2, 38.0, 38.0, 37.4, 38.3. This distribution shows no impressive tendency toward a particular value (lack of precision) but each value does come close to the actual temperature (high accuracy).

## Target Comparison

Accuracy is the degree of correctness, while precision is how strict that correctness is (or isn't) — how reproducible results are. For this example, consider results from a round of target practice.

Arrows are fired at a target, and measurements are taken in relation to the bull's eye at the center of the target. Accuracy describes how close the arrows are to the bull's-eye. The closer an arrow is to the bull's eye, the more accurate the shot.

How precise the shots are depends on how often the arrows land near each other on the target. When all or most arrows are grouped tightly together, the shots fired can be considered precise since they all landed near the same spot, if not necessarily near the bull's-eye. This is how results can indicate precision but not necessarily accuracy. However, it is important to note that it is not possible to reliably achieve accuracy without precision.

The target at left displays neither accuracy nor precision, while the target in the middle displays some precision but little accuracy. Finally, the third target, at right, shows both accuracy and precision.

## Number of Measurements

Accuracy can be improved by taking repeat measurements and taking an average. (This assumes that errors are randomly above and below the true value to the same degree). Therefore an experiment with a low degree of precision can provide accurate values where appropriate statics are applied.

Conversely, precision cannot be improved by taking repeated measurements but it is impossible to quantify precision without experimental repeats.

The danger when evaluating an experiment is that some errors are not random. In this case, an experiment could yield inaccurate results yet be highly precise.

## Quality

While a precise measurement may speak highly of an instrument's quality, an accurate reading will not reflect on the quality. Accuracy is an agreement of a measured value with an expected value. For example, a stopped clock will be accurate twice in day, but it will not be precise — i.e., able to consistently and accurately keep time throughout the day. In the case of a clock, how precisely it measures time matters a great deal and determines quality.