Accuracy vs Precision Explained
Accuracy is closeness to the true value. Precision is repeatability. Here is the difference, the dartboard analogy, and why both matter.
Last updated: 2026-05-21
“Accuracy” and “precision” are often used as if they mean the same thing. In measurement they describe two distinct qualities, and confusing them leads to bad data and wrong conclusions. A reading can be perfectly repeatable yet completely wrong. Understanding the difference is the foundation of every reliable measurement — and every reliable conversion.
Definitions
Accuracy is how close a measurement is to the true or accepted value. An accurate thermometer that reads 100°C in boiling water at sea level is reporting the correct answer. Accuracy is about being right.
Precision is how close repeated measurements are to one another, independent of whether they are correct. A scale that reads 5.02 g, 5.01 g, and 5.02 g for the same object is precise because the numbers agree, even if the object actually weighs 5.50 g. Precision is about being consistent.
The two are independent. You can have one without the other, both together, or neither — which is exactly what the dartboard analogy makes visible.
The Dartboard Analogy
Picture throwing darts at a board where the bullseye is the true value. Where the darts land tells you everything about accuracy and precision.
| Case | Where the darts land | What it means |
|---|---|---|
| Accurate & precise | Tight cluster on the bullseye | Right answer, every time — the goal of any measurement. |
| Precise, not accurate | Tight cluster, but off-center | Consistent and repeatable, yet consistently wrong. A systematic error. |
| Accurate, not precise | Scattered around the bullseye | Correct on average, but no single throw is trustworthy. Random scatter. |
| Neither | Scattered and off-center | Wrong and inconsistent — no useful information. |
The most dangerous case is “precise, not accurate.” The tight cluster looks convincing, so a biased instrument can be trusted long after it has drifted away from the truth.
Why the Difference Matters
The two problems have two different fixes. Accuracy is corrected by calibration: you compare the instrument against a known standard and remove the offset. If a scale reads 2 g high, calibrating against a certified mass shifts every future reading back onto the true value.
Precision is improved by better instruments and technique: a finer balance, controlled temperature and airflow, steadier handling, and more replicate readings all shrink the random scatter. Averaging many measurements raises precision but does nothing for a built-in bias — only calibration can fix that.
The same logic applies to working with units. A conversion is only as trustworthy as its source value and its conversion factor. When you need an exact factor you can rely on, our all converters use precise, standards-based ratios so the conversion never introduces error of its own.
Related Terms
A few neighboring concepts are easy to mix in with accuracy and precision:
- Resolution — the smallest change an instrument can display. A ruler marked in millimeters has higher resolution than one marked in centimeters. High resolution does not guarantee accuracy.
- Tolerance — the allowed deviation from a target, such as a bolt machined to 10.0 mm ± 0.1 mm. Tolerance defines how much error a result may have and still be acceptable.
- Systematic error — a consistent bias in one direction (a miscalibrated zero). It hurts accuracy and is the cause of “precise but not accurate” results.
- Random error — unpredictable scatter from noise or handling. It hurts precision and is reduced by averaging and better technique.
In short: aim for the bullseye (accuracy) and keep your throws tight (precision). Calibrate to fix bias, refine technique to fix scatter, and start every calculation from dependable numbers. Begin with all converters for conversion factors you can trust.