Which statement is true about accuracy and precision?

• A. A measurement can be precise and accurate even if biased.
• B. A measurement can be precise but not accurate if biased.
• C. A measurement can be accurate but not precise if inconsistent.
• D. Precision guarantees zero bias.

Answer: (B)

Concept being tested: accuracy vs. precision. Precision is about how repeatable or consistent measurements are, while accuracy is about how close those measurements are to the true value.

If a measurement is biased, it means there is a systematic offset from the true value. The results can be very consistent from trial to trial (high precision) but still off from the true value (not accurate). That’s exactly what the statement describes: measurements can be precise but not accurate if biased, because the bias shifts all results away from the true value even though they cluster tightly together.

To connect the other ideas briefly: a measurement cannot be accurate and biased at the same time, because bias means systematic error away from the true value. Precision does not guarantee zero bias, so high precision can occur with or without bias. An accurate result can happen with poor precision in some cases (results cluster near the true value on average but with wide spread), but that scenario is less universally true than the clear separation between precision (repeatability) and accuracy (closeness to true value) demonstrated by the biased-but-precise case.