In a set of repeated measurements, the root mean square mainly reflects the measurement's ______.

• A. accuracy
• B. precision
• C. stability
• D. bias

Answer: (B)

The key idea is that root mean square of a set of repeated measurements measures how tightly the results cluster together. That tight clustering reflects precision—the repeatability of the measurement process. A small RMS means the readings are consistent with each other, while a large RMS shows they vary a lot from one trial to the next.

This doesn't tell you how close those measurements are to the true value—that’s accuracy. You can have high precision but low accuracy if your measurements are consistently off by a bias. Stability is about how measurements behave over time, including any drift, which RMS over a single set doesn’t directly capture. So the RMS of repeated measurements mainly indicates precision.