Why Is Accuracy Different From Precision?

When we measure something, we usually want to know how close our result is to the actual value. But measurements can behave in different ways. A measuring instrument may give results that are very close to one another but still far from the correct value. Another instrument may produce results scattered around the correct value. This is why accuracy and precision are not the same thing.

Understanding the difference between accuracy and precision is important in science, engineering, medicine, manufacturing, and everyday measurements. Although the two words are often used together, they describe different qualities of a measurement.

What Is Accuracy?

Accuracy is a measure of how close a measured value is to the true or accepted value.

Suppose the actual length of a metal rod is exactly 10.00 cm. If a measurement gives 9.99 cm, the result is highly accurate because it is very close to the actual value.

For example:

True value = 10.00 cm
Measurement = 9.99 cm
Difference = 0.01 cm

The small difference means the measurement has high accuracy.

Accuracy is therefore concerned mainly with correctness. The closer a measurement is to the accepted value, the more accurate it is.

However, the true value is not always known exactly. In many scientific experiments, scientists use an accepted reference value or the best available value for comparison.

What Is Precision?

Precision describes how closely repeated measurements agree with one another.

Imagine measuring the same object five times and getting:

9.82 cm, 9.83 cm, 9.82 cm, 9.83 cm, and 9.82 cm.

These measurements are very close to each other. They are therefore highly precise.

But suppose the actual length is 10.00 cm. The measurements are consistently below the true value.

In this situation, the measurements have high precision but low accuracy.

Precision is therefore related to consistency or repeatability. It tells us how much repeated measurements vary from one another.

Accuracy and Precision Are Different

The easiest way to understand the difference is to think about a target.

Imagine throwing several darts at a target.

If the darts land close to the bullseye, your throws are accurate. If they land very close to one another, your throws are precise.

There are four possible situations.

High Accuracy and High Precision

The measurements are close to the true value and close to one another.

For example:

10.01 cm, 10.00 cm, 10.02 cm, 10.01 cm

If the accepted value is 10.00 cm, these measurements are both accurate and precise.

This is the ideal situation in scientific measurement.

High Precision but Low Accuracy

The measurements are very close to one another but far from the true value.

For example:

9.72 cm, 9.73 cm, 9.72 cm, 9.73 cm

If the true value is 10.00 cm, the results are consistent but incorrect.

This can happen when an instrument has a systematic error or has not been properly calibrated.

Low Precision but High Accuracy

Repeated measurements may be spread out, but their average can be close to the true value.

For example:

9.7 cm, 10.2 cm, 10.1 cm, 9.9 cm

If the true value is 10.00 cm, these results are scattered, so precision is relatively low. However, they are distributed around the correct value, giving reasonable overall accuracy.

Low Accuracy and Low Precision

The measurements are both far from the true value and widely scattered.

For example:

8.9 cm, 9.6 cm, 10.8 cm, 11.4 cm

Such measurements indicate poor measurement quality and may require investigation of the instrument, method, or experimental conditions.

Why Can a Measurement Be Precise but Not Accurate?

This is one of the most important ideas in measurement.

Suppose a weighing scale always shows 2 kg more than the actual mass. If you weigh an object several times, you might get:

52.0 kg, 52.0 kg, 52.1 kg, 52.0 kg

The readings are very close together, so the scale is precise.

But if the actual mass is 50.0 kg, the readings are not accurate.

The problem may be caused by a systematic error. A systematic error tends to affect measurements in a consistent direction.

Calibration problems, incorrect zero settings, and certain instrument errors can produce this type of result.

Why Can Measurements Be Accurate but Not Precise?

Random variations can make repeated measurements different from one another.

For example, suppose you measure a length several times using an instrument that is correctly calibrated, but your readings are affected by small changes in how you position the instrument.

You might obtain:

9.8 cm, 10.2 cm, 9.9 cm, 10.1 cm, and 10.0 cm.

The measurements are not tightly grouped, so their precision is limited. However, they are reasonably close to the true value.

This type of variation is often associated with random error.

Repeating measurements and calculating an average can help reduce the effect of random variation.

Accuracy, Precision, and Errors

Accuracy and precision are closely connected to the idea of measurement error.

Systematic errors mainly affect accuracy. If an instrument consistently gives readings that are too high or too low, measurements may be precise but inaccurate.

Random errors mainly affect precision. They cause repeated measurements to fluctuate.

For example, imagine a thermometer that always reads 2°C higher than the actual temperature. It may give very consistent readings, but those readings are inaccurate.

On the other hand, a thermometer that gives slightly different readings each time because of random fluctuations may have lower precision.

Recognizing the type of error helps scientists improve their measurement methods.

How Can Accuracy Be Improved?

Accuracy can often be improved by comparing measurements with a reliable reference and correcting systematic errors.

Some useful methods include:

Calibrating measuring instruments regularly
Checking and correcting zero error
Using reliable reference standards
Following the correct measurement procedure
Avoiding known sources of systematic error
Choosing a suitable measuring instrument

For example, if a balance does not read zero when nothing is placed on it, the zero error should be corrected before taking measurements.

How Can Precision Be Improved?

Precision can often be improved by reducing random variations.

Scientists may:

Repeat measurements several times
Use instruments with finer resolution
Keep experimental conditions stable
Follow the same procedure each time
Take care when reading scales
Calculate an average from repeated measurements

Repeating a measurement does not automatically make every individual reading more accurate. Instead, repeated measurements can help identify variation and produce a more reliable estimate.

Why Both Matter in Science

Scientists need both accuracy and precision because reliable measurements should be close to the correct value and reasonably consistent.

Imagine a laboratory measuring the concentration of a chemical solution. If the results are precise but inaccurate, the laboratory may repeatedly report the wrong concentration. If the results are accurate but poorly precise, individual measurements may vary too much to provide dependable results.

In engineering and manufacturing, the distinction is equally important. A machine may produce thousands of identical components, but if all of them have the wrong dimensions, consistency alone is not enough.

In medicine, accurate and precise measurements can also be important when monitoring quantities such as temperature, blood pressure, or laboratory values.

A Simple Way to Remember the Difference

A useful memory trick is:

Accuracy = How close to the correct value?

Precision = How close to each other?

Accuracy is about correctness.

Precision is about consistency.

You can be precise without being accurate, accurate without being highly precise, both, or neither.

Conclusion

Accuracy and precision describe two different aspects of measurement quality. Accuracy tells us how close a measurement is to the true or accepted value, while precision tells us how closely repeated measurements agree with one another.

A measurement can be highly precise but inaccurate when a systematic error affects every reading. It can also be reasonably accurate while having limited precision because of random variations.

Understanding this difference helps us interpret experimental results correctly and recognize problems with measuring instruments and methods. Whenever you see a set of measurements, do not simply ask whether the values are close to one another. Also ask whether they are close to the value they are supposed to represent.

That simple distinction is at the heart of reliable scientific measurement.

FAQs

What is the main difference between accuracy and precision?

Accuracy refers to how close a measured value is to the true or accepted value, while precision refers to how closely repeated measurements agree with one another. For example, if the actual length of an object is 10.00 cm and measurements are 9.99, 10.00, and 10.01 cm, they are both accurate and precise. If measurements are 9.70, 9.71, and 9.70 cm, they are precise because they are close together but not accurate because they are far from the true value. In simple terms, accuracy means correctness, while precision means consistency.

Can a measurement be precise but not accurate?

Yes, a measurement can be highly precise but not accurate. This happens when repeated measurements are very close to one another but consistently different from the true value. For example, suppose the actual mass of an object is 50.0 kg, but a faulty weighing scale repeatedly gives readings of 52.0, 52.1, and 52.0 kg. The readings are precise because they are close together, but they are inaccurate because they are not close to the actual mass. This situation is commonly associated with systematic errors, such as incorrect calibration or a constant zero error in the measuring instrument.

Can a measurement be accurate but not precise?

Yes. Measurements can be reasonably accurate while having low precision. This occurs when individual readings are spread out but remain relatively close to the true value. For example, if the actual value is 10.0 cm, measurements of 9.8, 10.2, 9.9, and 10.1 cm are reasonably accurate but not highly precise because they are not tightly grouped. Random errors can cause this type of variation. Taking several measurements and calculating their average can help provide a more reliable estimate of the true value while reducing the effect of random variations.

What is an example of high accuracy and high precision?

Suppose the accepted value of a measurement is exactly 20.00 cm. If repeated measurements give 19.99 cm, 20.00 cm, 20.01 cm, and 20.00 cm, the results demonstrate both high accuracy and high precision. They are highly accurate because they are very close to the accepted value. They are also highly precise because they are very close to one another. This is the ideal situation in scientific measurement. It indicates that the measuring instrument and experimental procedure are producing results that are both consistent and close to the value being measured.

How do systematic errors affect accuracy and precision?

Systematic errors mainly affect accuracy because they cause measurements to shift consistently away from the true value. For example, a balance that always adds 2 g to the actual mass may produce very consistent readings. Those readings can therefore be precise but inaccurate. Systematic errors may result from poor calibration, zero errors, incorrect instrument settings, or a consistent problem in the experimental method. Repeating the same measurement does not necessarily remove a systematic error. Instead, the source must be identified and corrected, often through calibration or comparison with a reliable reference standard.

How do random errors affect precision?

Random errors cause repeated measurements to vary unpredictably. As a result, they mainly reduce precision by making measurements less closely grouped. For example, when measuring the same length repeatedly, small differences in instrument positioning, reading the scale, environmental conditions, or other uncontrolled factors may produce slightly different values. Unlike a systematic error, a random error does not usually shift every measurement in the same direction. Taking multiple readings and calculating their average can reduce the influence of random variations. However, averaging does not automatically correct systematic errors that affect all measurements consistently.

Does a more precise instrument always give more accurate results?

No. A more precise instrument does not automatically produce more accurate results. An instrument may display very small differences between measurements and therefore provide highly consistent readings, but it can still be incorrectly calibrated. For example, a digital scale might consistently measure an object as 52.0 kg when its actual mass is 50.0 kg. The scale may provide precise readings but inaccurate results. Accuracy depends on how close the measurement is to the accepted value. Therefore, instruments should be properly calibrated and used correctly to achieve both high precision and high accuracy.

How can scientists improve accuracy?

Scientists can improve accuracy by reducing or correcting systematic errors. One important method is regular calibration, in which an instrument is compared with a known reference standard. Scientists can also check for zero errors, use suitable measuring instruments, follow standardized procedures, and control known sources of error. For example, before measuring mass with a balance, the balance should be checked to ensure that it reads zero when empty. Using appropriate reference values and carefully following experimental procedures can also improve accuracy. The goal is to make measurements as close as possible to the true or accepted value.

How can scientists improve precision?

Precision can often be improved by reducing random variation between repeated measurements. Scientists may take several readings instead of relying on a single measurement, keep experimental conditions stable, use instruments with suitable resolution, and follow the same procedure consistently. For example, measuring the length of an object several times and recording each result can reveal how much the measurements vary. Calculating an average can provide a more dependable estimate. However, precision is not simply about using more decimal places. A measurement with many digits is not necessarily precise unless repeated measurements show good agreement.

Why are accuracy and precision important in science?

Accuracy and precision are essential because scientific conclusions depend on reliable measurements. Accuracy helps scientists determine whether their results are close to the accepted value, while precision helps them determine whether repeated measurements are consistent. In laboratories, engineering, manufacturing, medicine, and research, poor accuracy or precision can lead to incorrect conclusions or unreliable products. Ideally, measurements should have both high accuracy and high precision. Understanding the difference also helps scientists identify whether problems are caused by systematic or random errors. By improving both qualities, researchers can obtain measurements that are more dependable and useful for scientific analysis.