Accuracy and precision are two important factors to consider when taking data measurements. Both accuracy and precision reflect how close a measurement is to an actual value, but accuracy reflects how close a measurement is to a known or accepted value, while precision reflects how reproducible measurements are, even if they are far from the accepted value.

You can think of accuracy and precision in terms of hitting a bullseye.

Accurately hitting the target means you are close to the center of the target, even if all of the marks are on different sides of the center. Precisely hitting a target means all the hits are closely spaced, even if they are very far from the center of the target. Measurements which are both precise and accurate are repeatable and very near true values.

### Definition of Accuracy

There are two common definitions of the term accuracy. In math, science, and engineering, accuracy refers to how close a measurement is to the true value.

The ISO (International Organization for Standardization) applies a more rigid definition, where accuracy refers to a measurement with both true and consistent results. The ISO definition means an accurate measurement has no systematic error and no random error. Essentially, the ISO advises the term accurate be used when a measurement is both accurate and precise.

### Definition of Precision

Precision is how consistent results are when measurements are repeated.

Precise values differ from each other because of random error, which is a form of observational error.

### Examples of Accuracy and Precision

You can think of accuracy and precision in terms of a basketball player. If the player always makes a basket, even though he strikes different portions of the rim, he has a high degree of accuracy.

If he doesn't make many baskets, but always strikes the same portion of the rim, he has a high degree of precision. A player who throws free throws that always make the basket the exact same way has a high degree of both accuracy and precision.

Take experimental measurements for another example of precision and accuracy. If you take the measurements of the mass of a 50.0-gram standard sample and get values of 47.5, 47.6, 47.5, and 47.7 grams, your scale is precise, but not very accurate. If your scale gives you values of 49.8, 50.5, 51.0, 49.6, it is more accurate than the first balance, but not as precise. The more precise scale would be better to use in the lab, providing you made an adjustment for its error.

### Mnemonic To Memorize the Difference

An easy way to remember the difference between accuracy and precision is:

- A
**C**curate is**C**orrect. (or**C**lose to real value) - P
**R**ecise is**R**epeating. (or**R**epeatable)

### Learn More

Accuracy and precision are only two important concepts used in scientific measurements. Two other important skills to master are significant figures and scientific notation. Scientists use percent error as one method of describing how accurate and precise a value is. It's a simple and useful calculation.