Physics · Ch 1 — Physical World and Measurement
Accuracy and Precision of Measuring Instruments
Accuracy and Precision of Measuring Instruments
Two Different Qualities of a Measurement
It is tempting to think that a "good" measurement is simply one made with a fine instrument,
but two genuinely different qualities are actually involved:
- Accuracy describes how close a measured value is to the true value of the quantity being measured. An accurate measurement has a small error (the difference between the measured and true values).
- Precision describes how close repeated measurements of the same quantity are to one another — i.e. how reproducible the measurement is, regardless of whether the value they cluster around is actually correct. A precise measurement has a small spread (scatter) among repeated readings.
Crucially, a measurement can be precise without being accurate, and (less commonly) can
happen to be accurate on average while being imprecise. The four-panel target diagram in this
section makes the distinction visual.
Illustration: Weighing an Object
Suppose the true mass of an object is exactly g.
- A balance that repeatedly reads g, g, g is precise (the readings are tightly clustered) but not accurate (they are all offset from the true value by about g — this offset is a systematic error, e.g. from an uncorrected zero error).
- A balance that reads g, g, g, g is scattered around close to the true value on average, so it is reasonably accurate, but it is not precise (the individual readings disagree with each other considerably). …
What this figure shows. A four-panel target/dartboard diagram, the classic own-drawn illustration of accuracy versus precision. Panel (a) shows a tight cluster of hits at the bull's-eye centre — both accurate and precise. Panel (b) shows a tight cluster of hits away from the centre, all in one corner of the board — precise (highly repeatable, low random error) but not accurate (a systematic offset from the true value). Panel (c) shows hits scattered widely but centred roughly on the bull's-eye — accurate on average but not precise (large random error, no systematic bias). Panel (d) shows hits scattered widely and off-centre — neither accurate nor precise. …