Scientific Thinking
Accuracy vs Precision
Accuracy and precision sound like synonyms, but in measurement they mean different things — and a result can have one without the other.
| Aspect | Accuracy | Precision |
|---|---|---|
| What it measures | Closeness to the true value | Consistency between repeated measurements |
| Answers the question | “Is it right?” | “Is it repeatable?” |
| Dartboard analogy | Darts centered on the bullseye | Darts tightly clustered (anywhere) |
| Improved by | Calibration against a known standard | Reducing random variation |
| Failure mode | A consistent bias (systematic error) | Scattered, noisy readings (random error) |
When to use accuracy
Accuracy matters most when the true value is what counts — a scale that always reads 2 kg high is precise but useless for knowing real weight.
When to use precision
Precision matters when you need repeatable, comparable readings — even a slightly off but consistent instrument can track change reliably.
Frequently asked questions
- Can something be precise but not accurate?
- Yes. A miscalibrated scale that reads 2 kg too high every time is highly precise (consistent) but inaccurate (wrong). Precision without accuracy points to a systematic error you can often correct with calibration.
- How do systematic and random errors relate?
- Systematic errors shift every reading the same way, hurting accuracy; random errors scatter readings, hurting precision. Averaging many readings reduces random error but never fixes a systematic one.
- Which matters more?
- It depends on the task. For a true measurement you need accuracy; for tracking change or comparing items you may need precision most. Ideally you want both.